Month: November 2023
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American International Group Inc. Has $502000 Stock Position in MongoDB, Inc. (NASDAQ:MDB)
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American International Group Inc. grew its position in MongoDB, Inc. (NASDAQ:MDB – Free Report) by 23.7% in the 2nd quarter, according to the company in its most recent Form 13F filing with the Securities and Exchange Commission (SEC). The firm owned 1,221 shares of the company’s stock after buying an additional 234 shares during the quarter. American International Group Inc.’s holdings in MongoDB were worth $502,000 at the end of the most recent quarter.
Several other hedge funds and other institutional investors also recently made changes to their positions in the company. Raymond James & Associates lifted its position in shares of MongoDB by 32.0% in the first quarter. Raymond James & Associates now owns 4,922 shares of the company’s stock worth $2,183,000 after purchasing an additional 1,192 shares in the last quarter. PNC Financial Services Group Inc. raised its position in MongoDB by 19.1% during the first quarter. PNC Financial Services Group Inc. now owns 1,282 shares of the company’s stock valued at $569,000 after acquiring an additional 206 shares in the last quarter. MetLife Investment Management LLC bought a new position in MongoDB during the first quarter valued at approximately $1,823,000. Panagora Asset Management Inc. raised its position in MongoDB by 9.8% during the first quarter. Panagora Asset Management Inc. now owns 1,977 shares of the company’s stock valued at $877,000 after acquiring an additional 176 shares in the last quarter. Finally, Vontobel Holding Ltd. raised its position in MongoDB by 100.3% during the first quarter. Vontobel Holding Ltd. now owns 2,873 shares of the company’s stock valued at $1,236,000 after acquiring an additional 1,439 shares in the last quarter. 88.89% of the stock is currently owned by institutional investors and hedge funds.
Wall Street Analysts Forecast Growth
MDB has been the topic of a number of recent analyst reports. Royal Bank of Canada reissued an “outperform” rating and issued a $445.00 price target on shares of MongoDB in a research report on Friday, September 1st. Argus lifted their price target on shares of MongoDB from $435.00 to $484.00 and gave the company a “buy” rating in a research report on Tuesday, September 5th. Barclays lifted their price target on shares of MongoDB from $421.00 to $450.00 and gave the company an “overweight” rating in a research report on Friday, September 1st. Macquarie raised their price objective on shares of MongoDB from $434.00 to $456.00 in a research note on Friday, September 1st. Finally, Citigroup raised their price objective on shares of MongoDB from $430.00 to $455.00 and gave the stock a “buy” rating in a research note on Monday, August 28th. One investment analyst has rated the stock with a sell rating, two have assigned a hold rating and twenty-four have issued a buy rating to the company. According to data from MarketBeat.com, the company presently has a consensus rating of “Moderate Buy” and an average target price of $419.74.
View Our Latest Stock Report on MDB
Insider Activity
In related news, CRO Cedric Pech sold 16,143 shares of the business’s stock in a transaction that occurred on Thursday, September 7th. The shares were sold at an average price of $378.86, for a total transaction of $6,115,936.98. Following the completion of the transaction, the executive now owns 34,418 shares in the company, valued at $13,039,603.48. The sale was disclosed in a filing with the SEC, which can be accessed through the SEC website. In related news, CRO Cedric Pech sold 16,143 shares of the business’s stock in a transaction that occurred on Thursday, September 7th. The shares were sold at an average price of $378.86, for a total transaction of $6,115,936.98. Following the completion of the transaction, the executive now owns 34,418 shares in the company, valued at $13,039,603.48. The sale was disclosed in a filing with the SEC, which can be accessed through the SEC website. Also, CEO Dev Ittycheria sold 100,500 shares of the business’s stock in a transaction that occurred on Tuesday, November 7th. The shares were sold at an average price of $375.00, for a total transaction of $37,687,500.00. Following the transaction, the chief executive officer now owns 214,177 shares of the company’s stock, valued at approximately $80,316,375. The disclosure for this sale can be found here. Insiders sold a total of 289,484 shares of company stock valued at $101,547,167 in the last ninety days. 4.80% of the stock is owned by insiders.
MongoDB Trading Up 0.9 %
MDB opened at $392.57 on Friday. The firm has a 50 day simple moving average of $354.09 and a 200 day simple moving average of $355.78. MongoDB, Inc. has a fifty-two week low of $137.70 and a fifty-two week high of $439.00. The company has a market cap of $28.01 billion, a price-to-earnings ratio of -113.46 and a beta of 1.16. The company has a debt-to-equity ratio of 1.29, a current ratio of 4.48 and a quick ratio of 4.48.
MongoDB (NASDAQ:MDB – Get Free Report) last posted its quarterly earnings results on Thursday, August 31st. The company reported ($0.63) earnings per share (EPS) for the quarter, topping the consensus estimate of ($0.70) by $0.07. The business had revenue of $423.79 million for the quarter, compared to analyst estimates of $389.93 million. MongoDB had a negative return on equity of 29.69% and a negative net margin of 16.21%. On average, sell-side analysts anticipate that MongoDB, Inc. will post -2.17 earnings per share for the current year.
MongoDB Company Profile
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
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SolarWinds, a provider of observability and IT management software, has made enhancements to the Database Observability capability within the cloud-based SolarWinds Observability platform which provides visibility into open-source, cloud-enabled, and NoSQL databases to identify and address costly and critical threats to their systems and business, the firm said.
Database Observability is part of the SolarWinds Database Performance Management portfolio, which includes SQL Sentry and Database Performance Analyzer.
“Database performance is critical to the success of an organization’s IT strategy and business operations. However, databases also lead to some of the most complex challenges that IT teams face due to the complicated, business-critical, and difficult-to-diagnose issues they often present,” the company said.
“Without complete and precise database monitoring and observability, IT and DevOps teams struggle to accurately diagnose the root cause of performance issues, risking costly downtime, decreased quality of service delivery, and other critical threats to health and growth potential of the entire enterprise.”
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Equities researchers at Wells Fargo & Company assumed coverage on shares of MongoDB (NASDAQ:MDB – Get Free Report) in a research report issued on Thursday, MarketBeat.com reports. The firm set an “overweight” rating and a $500.00 price target on the stock. Wells Fargo & Company‘s price target would indicate a potential upside of 27.37% from the company’s previous close.
Several other research analysts also recently issued reports on MDB. Scotiabank began coverage on shares of MongoDB in a research report on Tuesday, October 10th. They set a “sector perform” rating and a $335.00 price objective on the stock. Morgan Stanley raised their price objective on shares of MongoDB from $440.00 to $480.00 and gave the stock an “overweight” rating in a research report on Friday, September 1st. Needham & Company LLC raised their price objective on shares of MongoDB from $430.00 to $445.00 and gave the stock a “buy” rating in a research report on Friday, September 1st. Stifel Nicolaus raised their target price on shares of MongoDB from $420.00 to $450.00 and gave the stock a “buy” rating in a research note on Friday, September 1st. Finally, Capital One Financial upgraded shares of MongoDB from an “equal weight” rating to an “overweight” rating and set a $427.00 target price for the company in a research note on Wednesday, November 8th. One equities research analyst has rated the stock with a sell rating, two have issued a hold rating and twenty-four have assigned a buy rating to the stock. According to data from MarketBeat.com, MongoDB presently has a consensus rating of “Moderate Buy” and a consensus target price of $419.74.
Check Out Our Latest Research Report on MongoDB
MongoDB Trading Up 0.9 %
NASDAQ MDB opened at $392.57 on Thursday. The company has a debt-to-equity ratio of 1.29, a current ratio of 4.48 and a quick ratio of 4.48. The firm’s fifty day moving average price is $354.09 and its 200 day moving average price is $355.78. The company has a market capitalization of $28.01 billion, a price-to-earnings ratio of -113.46 and a beta of 1.16. MongoDB has a 12 month low of $137.70 and a 12 month high of $439.00.
MongoDB (NASDAQ:MDB – Get Free Report) last posted its earnings results on Thursday, August 31st. The company reported ($0.63) EPS for the quarter, beating analysts’ consensus estimates of ($0.70) by $0.07. The firm had revenue of $423.79 million for the quarter, compared to the consensus estimate of $389.93 million. MongoDB had a negative net margin of 16.21% and a negative return on equity of 29.69%. On average, sell-side analysts expect that MongoDB will post -2.17 earnings per share for the current fiscal year.
Insiders Place Their Bets
In other MongoDB news, CRO Cedric Pech sold 308 shares of MongoDB stock in a transaction dated Wednesday, September 27th. The shares were sold at an average price of $326.27, for a total transaction of $100,491.16. Following the completion of the transaction, the executive now owns 34,110 shares in the company, valued at $11,129,069.70. The sale was disclosed in a document filed with the SEC, which is accessible through this hyperlink. In other news, CRO Cedric Pech sold 308 shares of MongoDB stock in a transaction dated Wednesday, September 27th. The shares were sold at an average price of $326.27, for a total transaction of $100,491.16. Following the completion of the sale, the executive now directly owns 34,110 shares in the company, valued at $11,129,069.70. The sale was disclosed in a legal filing with the SEC, which is accessible through this link. Also, Director Dwight A. Merriman sold 2,000 shares of MongoDB stock in a transaction dated Tuesday, November 7th. The stock was sold at an average price of $365.30, for a total transaction of $730,600.00. Following the sale, the director now owns 1,189,159 shares of the company’s stock, valued at $434,399,782.70. The disclosure for this sale can be found here. Over the last quarter, insiders sold 289,484 shares of company stock worth $101,547,167. Insiders own 4.80% of the company’s stock.
Institutional Investors Weigh In On MongoDB
A number of hedge funds and other institutional investors have recently modified their holdings of the company. Jacobs Levy Equity Management Inc. purchased a new stake in MongoDB in the third quarter valued at approximately $2,453,000. Creative Planning grew its holdings in MongoDB by 2.3% in the third quarter. Creative Planning now owns 5,139 shares of the company’s stock valued at $1,777,000 after purchasing an additional 114 shares during the period. Jag Capital Management LLC purchased a new stake in MongoDB in the third quarter valued at approximately $424,000. Mercer Global Advisors Inc. ADV grew its holdings in MongoDB by 10.1% in the third quarter. Mercer Global Advisors Inc. ADV now owns 11,521 shares of the company’s stock valued at $3,985,000 after purchasing an additional 1,060 shares during the period. Finally, Toroso Investments LLC grew its holdings in MongoDB by 10.3% in the third quarter. Toroso Investments LLC now owns 3,010 shares of the company’s stock valued at $1,041,000 after purchasing an additional 281 shares during the period. 88.89% of the stock is currently owned by hedge funds and other institutional investors.
MongoDB Company Profile
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
Further Reading
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MDB Stock: AI Potential Powers MongoDB To 98% Gain This Year – Investor’s Business Daily
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MongoDB
MongoDB
MDB
$2.95
0.76%
29%
IBD Stock Analysis
- Stock working on handle at around 400
- Week’s high of 402.70 could be early entry
Industry Group Ranking
Emerging Pattern
Consolidation
* Not real-time data. All data shown was captured at
12:00PM EST on
11/17/2023.
MongoDB (MDB) is the IBD Stock of the Day for Friday, as MDB stock forms a consolidation pattern and nears adding a handle. The database software player is primed to benefit from the coming artificial intelligence boom that will require vast amounts of data, according to analysts.
X
MDB stock is up just under 1% at 392.28 on the stock market today.
MongoDB shares have gained 98% on the year entering trading Friday. The stock is also on the IBD 50 and IBD Tech Leaders lists.
MDB Stock: Sizing Up AI Potential
New York-based MongoDB’s main platform, Atlas, is built on NoSQL. The document-based data platform gives developers flexibility and the ability to store vast amounts of data, the company says. It also works across multiple cloud platforms.
Wall Street considers MongoDB a potential AI winner, with the ability to capture more share in a massive database market.
“MongoDB is a best-of-breed next generation database vendor that is well-positioned in the rapidly growing NoSQL unstructured database market,” BofA Securities analyst Brad Sills wrote in a client note last month.
Sills initiated coverage with a buy rating and a target price of 450 in an October client note.
As more companies adopt generative artificial intelligence products, Sills says the volume and sophistication of data applications will increase.
“This should serve as a tailwind for MongoDB, given the platform’s flexible document model to handle complex data structures and evolving data models,” Sills wrote.
On Thursday, Wells Fargo initiated coverage of MongoDB with a buy rating, according to Seeking Alpha, citing MDB’s potential as an AI play.
Earnings On Deck
MongoDB will report earnings for its August through October quarter on Dec. 5. Analysts expect adjusted earnings to climb 121% year over year to 51 cents per share, according to FactSet. Sales are expected to increase 22% to $406 million.
Barclays analyst Raimo Lenschow said in a client note this week that MongoDB has “a nice setup” against conservative guidance for its fiscal third quarter. But he cautioned that shares are already up significantly this year and have gained about 13% following strong earnings from fellow software firm Datadog (DDOG) on Nov. 7.
That stock performance, “does not leave a lot of room for error,” Lenschow wrote. “As a result, we are probably more cautious for this quarter.”
For its quarter ending in July, MongoDB reported adjusted earnings of 93 cents a share, more than doubling Wall Street’s prediction for 46 cents, according to FactSet. Sales jumped 40% to $423.8 million, vs. expectations of $394 million
“We are at the early stages of AI powering the next wave of application development,” MongoDB President and Chief Executive Dev Ittycheria said in the Aug. 31 news release. “We believe MongoDB provides developers a unified platform that supports both the foundational requirements necessary for any application and the exceptionally demanding needs of AI-specific applications.”
MDB Stock: Consolidation Pattern
MDB is in a consolidation pattern with a buy point of 439, according to MarketSmith. If MDB can hold back for a couple more days, it’ll have a handle with a lower official buy point of 402.70. But if MongoDB goes before then, investors could still use that 402.70 as an early entry.
MongoDB stock has a best-possible IBD Composite Rating of 99, measuring fundamental and technical performance.
Further, MDB shares have a strong Relative Strength Rating of 98, according to IBD Stock Checkup. The score puts MDB stock in the top 2% of all stocks when it comes to 12-month performance.
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Microsoft’s ‘iPhone Moment’: Shares Dip But Analysts Remain Positive After Ignite Event – Benzinga
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Microsoft’s MSFT shares were lower in morning trade on Friday. Tech stocks were sold off on all the major indices.
This week, the company held its annual Ignite conference. It unveiled a range of new and updated artificial intelligence (AI) and cloud offerings. One analyst equated the Copilot, the company’s AI assistant based around Bing Chat, to an “iPhone moment.”
KeyBanc analyst Michael Turits maintains an overweight rating and a $420 price target, while Piper Sandler analyst Brent Bracelin made no change to the company’s overweight rating and $425 price target.
Here are their takes on the event.
- KeyBanc: Turits praised Copilot’s additional segments and two new Azure Chips — Azure Maia, built for generative AI tasks, and Azure Cobalt designed to run workloads on Microsoft Cloud. These announcements are “a positive step” in improving overall cloud and AI workload performance, he said. They also reduce the higher costs associated with generative AI tasks.
- Piper Sandler: Bracelin was impressed with the new chip rollouts and Microsoft’s increasing security ambitions. He detected “early signs of enterprise FOMO and risk of falling behind that could in turn help justify higher AI budgets into 2024 and 2025.” News flow from day two of the conference will be favorable for MongoDB MDB and Oracle ORCL as tailwinds begin to surface across the database layer.
The Wolfe Byte
Wolfe believes Microsoft may have created an “iPhone moment” for Copilot.
“We view the potential for Microsoft to monetize Copilots across the entire customer base because the incremental functionality, network effect and ability to integrate across every application is quite literally a killer-app.”
Copilot could create a double-digit upside to both FY2026 consensus revenue and earnings per share.
“Copilot’s connectivity to other applications creates a first-mover advantage that will enable MSFT to dominate wallet and mind-share and create incremental friction for other SaaS vendors to monetize their own agents.”
Price Action: Microsoft’s stock fell 1.16% to $371.80 on Friday. However, the Redmond, Washington-based company saw its stock climb 9.8% since the end of October.
Now Read: What’s Going On With Nvidia Stock? Bill & Melinda Gates Foundation Buy $4M Stake
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A look at some of the best database and RDBMS tools for Java software developers. Learn more about Java and database programming.
Java developers often rely on specific database tools to efficiently manage data storage, retrieval and manipulation. In this tutorial, we explore some of the top database tools for Java developers, specifically Grails, Struts, Java DB and MongoDB.
Jump to:
Grails: Best web application framework for integrations
Grails, a web application framework built on the Groovy programming language, offers significant assistance with database development in Java through its integrated features and tools. It simplifies database interactions, making it easier for developers to work with databases in their applications.
Pricing
Grails is an open-source web application framework and is free to use. That being said, Grails, maintained by the Grails Foundation, does offer commercial support, with varying degrees of support available depending on the version you are using:
- Version 6: Standard support available until June 2025.
- Version 5: Standard support available until June 2024.
- Versions 1-4: Premium support.
It should be noted that Standard Support pricing begins at $150 per hour. Premium Support, meanwhile, requires a custom quote and can be obtained via the Grails Support page.
Features
Grails has quite a few pros worth discussing. They include:
- Grails Object-Relational Mapping: GORM is a powerful Object-Relational Mapping framework that comes integrated with Grails. It provides a high-level, developer-friendly API for interacting with databases. GORM abstracts away the complexities of SQL queries and database operations, allowing developers to work with domain objects instead of raw database tables. This makes code more intuitive, maintainable and less error-prone.
- Domain classes: In Grails, domain classes are the central component for defining data models. These classes represent database tables and provide an easy way to define relationships, constraints and validations. With GORM, developers can create, read, update and delete records in the database using simple methods on domain objects, making database operations more straightforward.
- Automatic schema generation: Grails can automatically generate database schemas based on the defined domain classes. This means developers don’t need to write SQL scripts for creating tables, columns and relationships. Grails and GORM take care of synchronizing the schema with the domain classes, saving developers time and effort.
- Dynamic finders and querying: GORM supports dynamic finders, which allow developers to query the database using concise and readable syntax. For example, you can find a user by their username using a method like User.findByUsername(‘john’). Additionally, GORM supports a powerful query language, Criteria API, and named queries, giving developers various options for constructing complex queries.
- Data source configuration: Grails provides configuration options to define data sources for different environments (development, testing and production). This enables developers to switch between databases easily based on the environment. The configuration is typically done in the application.yml or application.groovy file.
Pros
Some of Grails pros include:
- Multi-database support: Grails supports multiple databases out of the box. Developers can configure different data sources for different parts of the application, such as using a relational database for one module and a NoSQL database for another. This flexibility is useful when dealing with microservices architectures or hybrid data storage needs.
- Validation and constraints: Grails offers built-in support for defining constraints and validations on domain classes. These constraints help ensure data integrity and consistency. GORM validates data before saving it to the database, preventing invalid or inconsistent data from being persisted.
- Database migration: Grails provides tools for managing database schema changes over time. The database-migration plugin allows developers to version-control their database schema changes and apply them to different environments easily.
- Integration with Spring ecosystem: Grails is built on top of the Spring Framework, which means it can seamlessly integrate with various Spring components and libraries, including Spring Data and Spring Security. This integration enhances the capabilities of Grails in terms of database access and other functionalities.
Cons
Grails notable cons are:
- Smaller community: This results in fewer learning resources and less documentation.
- Fewer plugins, add-ons and modules than other frameworks in its class: This leads to potential for less functionality.
- Works with runtime languages: This makes the tool more error-prone.
Struts: Best Model-View-Controller framework
Struts is a widely used web application framework based on the MVC architecture. While Struts itself doesn’t have built-in database-specific features like Grails’ GORM, it does provide a framework that allows developers to integrate various database tools and libraries effectively.
Pricing
Like other Java database tools on our list, Struts is open-source and free to use. Commercial support is available, and developers can find a list of commercial support providers on the Struts Support page.
Features
Struts is known for its rich set of features, which include:
- MVC architecture: Struts follows the MVC design pattern, which encourages the separation of concerns in an application. This separation makes it easier to manage database-related code independently of other components. The Model component in MVC represents the data and its interactions with the database.
- Action classes: In Struts, action classes handle user requests and serve as an intermediary between the user interface (View) and the data model (Model). Developers can integrate database-related code within action classes to perform Create, Read, Update, Delete operations and other database interactions.
- Data access objects: Struts applications can incorporate DAO design patterns to encapsulate database interactions in separate classes. These DAOs act as a bridge between the application and the database. By using DAOs, developers can centralize database-related code, enhancing modularity and code reusability.
- Data source configuration: Similar to other Java applications, Struts applications can configure data sources for different environments (e.g., development, testing and production). This configuration allows developers to manage database connections effectively and switch between databases as needed.
Pros
Some of Struts main pros for Java developers include:
- Integration with Java Database Tools:
- Java Database Connectivity: Struts applications can make use of the core JDBC API to interact with relational databases. JDBC provides a low-level interface for executing SQL queries, managing connections and handling transactions. Developers can integrate JDBC code within action classes to perform database operations.
- Spring JDBC: Struts developers often leverage Spring JDBC, an extension of the core JDBC API. Spring JDBC simplifies database interactions by offering features like exception handling, connection pooling and simplified error management. It provides higher-level abstractions over raw JDBC, making database code more readable and maintainable.
- Validation and data integrity: Struts offers validation mechanisms that help ensure the integrity of data before it’s persisted in the database. By validating user input and data consistency, Struts helps prevent invalid or erroneous data from being stored.
- Use of ORM tools: Although Struts lacks an integrated ORM tool like GORM in Grails, developers can choose to integrate third-party ORM tools like Hibernate or Java Persistence API with their Struts applications. These ORM tools offer higher-level abstractions for database interactions, simplifying the process of mapping Java objects to database tables.
- Integration with Spring ecosystem: Struts applications can also benefit from integrating with the Spring ecosystem, which offers a wide range of tools and modules for various aspects of Java development, including database interactions. Spring components like Spring Data and Spring JDBC can enhance the capabilities of Struts applications in terms of database access.
Cons
Despite its benefits, Struts does have some cons:
- Scalability: Struts is known for lacking in the scalability department, partially due to its use of a single action servlet. Consider this if you are working on projects that will need to scale up.
- The Struts framework lacks a backward flow.
- Challenging for beginners: It is considered difficult for newer programmers and developers with little experience using frameworks.
- Lack of transparency: Understanding the inner workings of the framework can be a challenge as many of its processes run in the background and may take some digging to uncover.
Java DB (Apache Derby): Best for relational database systems
Java DB, also known as Apache Derby, is a relational database management system that offers support for Java applications. It provides a lightweight and embedded database solution that can be easily integrated into Java applications.
Pricing
Java DB is an open-source tool and is free to use under the Apache License.
Features
Java DB assists with database development in Java by offering the following features and benefits:
- Embeddable nature: Java DB is designed to be embedded within Java applications. This means that the database runs within the same Java Virtual Machine as the application itself, eliminating the need for separate database server processes. This embedded approach simplifies deployment and eliminates the complexities associated with managing external database servers.
- Small footprint: Java DB is compact in terms of memory usage and storage footprint. This makes it suitable for resource-constrained environments, such as embedded systems, desktop applications and mobile applications.
- Java API integration: Java DB provides a Java API that allows developers to manage the database programmatically. This API allows for tasks such as connecting to the database, executing SQL queries, managing transactions and handling errors.
- ACID compliance: Java DB ensures the ACID properties (Atomicity, Consistency, Isolation, Durability) of transactions. This guarantees that database operations are reliable and maintain data integrity even in the face of failures.
- Network server mode: While the embedded mode is suitable for many scenarios, Java DB also supports a network server mode. In this mode, Java DB operates as a separate database server that multiple applications can connect to simultaneously. This mode is useful when applications need to access the database from different JVMs or over a network.
- Cross-platform compatibility: Java DB is designed to be platform-independent, meaning that applications developed on one platform can easily be transferred to another platform without major modifications. This portability can be a huge time saver in cross-platform development.
- Database management tools: Java DB provides tools for managing databases, including command-line utilities and graphical user interfaces. These tools allow developers to perform tasks such as querying the database, managing data and monitoring performance.
Pros
Java DB is known for the following pros:
- Ease of integration: Java DB seamlessly integrates with Java applications through standard JDBC APIs. Developers can use familiar Java classes and interfaces to interact with the database, making it straightforward to perform database operations such as creating tables, inserting data, querying and updating records.
- Zero configuration: Java DB often requires minimal configuration. It supports automatic schema generation, which means that developers don’t need to write SQL scripts to create tables and relationships. Java DB can automatically generate the necessary schema based on defined domain classes or entities.
- Scalability and performance: While Java DB is often used for small to medium-sized applications, it can handle larger datasets and workloads when configured appropriately. However, for extremely large-scale applications, other enterprise-grade databases might be more suitable.
Cons
Java DB is not without its cons, which include:
- Lack of index support: Columns defined as CLOB, BLOB or LONG VARCHAR data types do not support indexes.
- Disk space: Database developers will encounter a “LogFull” error if the database log is unable to allocate adequate disk space, causing the system to crash or shut down. This error is not always visible, so always be aware of system resource limitations.
- Not well-suited for larger projects: Due to its lightweight nature, it is not always an ideal choice for larger projects but works fine for small to medium ones.
MongoDB: Best for NoSQL-backed applications
MongoDB, a popular NoSQL database, offers significant advantages for database development in Java applications. It diverges from traditional relational databases by using a document-oriented data model and JSON-like documents for data storage. MongoDB’s flexibility and scalability make it a powerful choice for Java developers.
Pricing
MongoDB has two pricing options, with multiple tiers under each option. While we highlight the basics below, we recommend visiting the MongoDB Pricing page for a full list of pricing options.
MongoDB Atlas
- Serverless: $0.10/million reads.
- Dedicated: $57/month.
- Shared: Starts at $0/month.
MongoDB Enterprise is also available. Developers can contact sales for more information.
Features
Here are just a few of the ways that MongoDB helps with database development in Java:
- Schema flexibility: MongoDB’s document-oriented model allows Java developers to work with dynamic schemas. This means that documents within a collection can have varying structures, making it easier to accommodate changes in data requirements without altering the database schema.
- JSON-like documents: MongoDB’s use of JSON-like documents aligns well with Java’s data structures. Developers can often directly map Java objects to MongoDB documents, simplifying the process of storing and retrieving data.
- Official Java driver: MongoDB provides an official Java driver that offers a comprehensive set of APIs for interacting with the database. Java developers can use this driver to perform CRUD operations, aggregations, indexing and more.
- Embedded documents and arrays: MongoDB supports embedded documents and arrays within documents. This is useful for modeling complex data structures, such as storing arrays of objects directly within a document. Java developers can work with these structures using the driver’s APIs.
- Spring Data MongoDB: Java developers using MongoDB can benefit from Spring Data MongoDB, an extension of the Spring Framework. It provides higher-level abstractions for working with MongoDB, reducing boilerplate code and offering features like querying, indexing and repository support.
Pros
Pros of MongoDB include:
- Auto-sharding and scalability: MongoDB offers built-in support for horizontal scaling through auto-sharding. This means that as data grows, MongoDB can distribute it across multiple nodes or servers, providing high availability and improved performance.
- Replication and high availability: MongoDB supports data replication to ensure data durability and high availability. Java developers can configure replica sets to automatically maintain copies of data across different nodes. If one node fails, the replica set can promote a secondary node to become the primary, ensuring continuity.
- Geospatial data: MongoDB supports geospatial data and queries, making it suitable for applications that require location-based features. Java developers can use the Java driver to perform geospatial queries and store location data effectively.
Cons
MongoDB has several cons that should be considered:
- Limited data size: Documents are limited to 16MB in MongoDB, so keep this in mind if you are working with larger documents.
- Duplication and relational issues: MongoDB is known to have issues with duplicate data and relations that are not well-defined. This can lead to data corruption if not properly mitigated.
- Need substantial data storage space: MongoDB tends to require a large amount of data storage because of the above-mentioned duplication problem.
Final thoughts on top database tools for Java developers
Tools like Grails, Struts, Java DB and MongoDB provide essential abstractions, interfaces and functionalities that abstract the complexities of database management. From GORM and Hibernate in the Grails ecosystem to JDBC and Spring JDBC in Struts applications, these tools empower developers to interact with databases effectively. As the software landscape evolves, staying up-to-date with the latest tools and best practices is essential for successful Java development.
MMS • RSS
Posted on nosqlgooglealerts. Visit nosqlgooglealerts
What are the 4 NoSQL types?
NoSQL, short for “not only SQL,” is a type of database management system that provides a flexible and scalable approach to storing and retrieving data. Unlike traditional relational databases, NoSQL databases are designed to handle large volumes of unstructured and semi-structured data. There are four main types of NoSQL databases, each with its own unique characteristics and use cases.
1. Key-Value Stores:
Key-value stores are the simplest form of NoSQL databases. They store data as a collection of key-value pairs, where each key is unique and associated with a value. These databases offer fast and efficient data retrieval based on the key. Key-value stores are commonly used for caching, session management, and storing user preferences.
2. Document Databases:
Document databases store data in a semi-structured format, typically using JSON or XML documents. Each document can have a different structure, allowing for flexibility in data modeling. Document databases excel at handling unstructured data, making them suitable for content management systems, real-time analytics, and collaborative applications.
3. Column-Family Stores:
Column-family stores organize data into columns rather than rows, making them ideal for handling large amounts of data with varying structures. They are highly scalable and provide fast read and write operations. Column-family stores are commonly used for time-series data, log storage, and data warehousing.
4. Graph Databases:
Graph databases are designed to represent and store relationships between entities. They use nodes to represent entities and edges to represent relationships between nodes. Graph databases excel at traversing complex relationships and are commonly used for social networks, recommendation engines, and fraud detection.
FAQ:
Q: What is the main difference between NoSQL and SQL databases?
A: The main difference lies in their data models. SQL databases use a structured, tabular format, while NoSQL databases offer more flexibility in handling unstructured and semi-structured data.
Q: Are NoSQL databases suitable for all types of applications?
A: NoSQL databases are particularly well-suited for applications that require scalability, high availability, and fast data retrieval. However, they may not be the best choice for applications that heavily rely on complex transactions and strict data consistency.
Q: Can I use multiple types of NoSQL databases in a single application?
A: Yes, it is possible to use multiple types of NoSQL databases within a single application. This approach, known as polyglot persistence, allows developers to leverage the strengths of different database types for different parts of their application.
In conclusion, NoSQL databases offer a range of options for storing and retrieving data, each with its own strengths and use cases. Whether you need fast key-value lookups, flexible document storage, scalable column-based data handling, or powerful graph-based relationships, there is a NoSQL database type that can meet your specific needs.
MMS • Dion Stewart Joel Tosi
Article originally posted on InfoQ. Visit InfoQ
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Transcript
Shane Hastie: Good day, folks. This is Shane Hastie with InfoQ Engineering Culture Podcast. Today I’m sitting down with Dion Stewart and Joel Tosi. Dion, Joel, thanks for taking the time to talk to us today. My normal starting point is who’s Dion? Who’s Joel? So let’s start with Dion. Who’s Dion?
Introductions [00:23]
Dion Stewart: Hi, Shane. Thanks for having us. Yeah, I am a developer/coach. I started off my technical career back in the 1990s as a small talk developer. I learned small talk at the University of St. Thomas in St. Paul, Minnesota from a guy named Dave West. One of the reasons I bring that up is there are some InfoQ articles about Dave West and in particular an experimental program that he initiated at Highlands University in New Mexico. So I think there’s a couple articles on the InfoQ site still about that. That’s pertinent because that apprenticeship program that he ran has a lot of similarities with this Dojo model of experiential and immersive learning that Joel and I have been part of.
The other thing I’ll say about Dave West and my experience at the University of St. Thomas is this predated Java. So at the time, there were really only two games in town for commercial OO development, C++, which a lot of Smalltalkers say isn’t really OO. But anyway, that and Smalltalk. Dave was bringing people like Ward Cunningham and Kent Beck and Rebecca Wirfs-Brock, these luminaries onto campus. And as a result of that, I got exposed to test-driven development and continuous integration and some other practices that eventually made their way into extreme programming. I was exposed to them even before extreme programming was a thing.
In the ’90s, I was purely a developer. In the early aughts, I kind of moved into this player coach role where I would be put on teams as a developer, but I was also sort of nudged with a wink, “Hey, teach these folks automated testing and TDD and some of these other practices.” Around 2010, I started full-time coaching. I coached for David Hussman. Sadly we’ve lost him now, but he had a company in Minneapolis called DevJam. That’s where I met Joel. And around 2015, Joel and I were part of this thing called the Dojo at Target, which I’ll leave that for later. We’ll get into that.
And then the last thing I’ll say is my partnership with Joel, we’ve written two books. The first one was on Dojos, it was called Creating Your Dojo. And then the one we released earlier this year is called Coaching for Learning.
Shane Hastie: Welcome. Joel?
Joel Tosi: Typical engineer by trade. Spent the early 2000s with a mercantile exchange in Chicago, so low latency, high throughput systems, all of that kind of fun stuff. Engineer manager. I was a really bad manager, but that’s beside the point. Then I went back into architect. When I was an architect for Mercantile Exchange, that’s actually where I met David Hussman. And at the Mercantile Exchange, we were trying to figure out how do we get better at some of these engineering practices. Got lucky and met David. Had a great relationship there, trying a lot of ways of better engineering practices, which was always fun with really risky scenarios as well as really complex environments. When I left the Mercantile Exchange, went to Red Hat for about a year or two, was a North American architect, began kind of helping organizations design and implement systems.
When I left Red Hat, I remember speaking to a lot of my friends that are great engineers, but I always felt like Red Hat was great technology but wasn’t great products. And they’d always ask me, like, “What do you mean by that?” I go like, “I just don’t feel like we have beautiful technology. But the way people want to use it, we’re not building it how people want to use it. We’re just building really cool things.” And I think that was partially David rubbing off on me because David and I became good friends over the years. And so then left Red Hat, started working more closely with David, usually doing more of the engineering side of things, but also really just help teams understand their product and then kind of embrace more simplicity. How do we get bigger impact, but keep the code clean and make it easy for us to do things? And just really easy to build guidance into the dojos, hung out with Dion and the rest of is history.
Shane Hastie: Cool. I’d like to just take us on a slight deviation. Dave Hussman, the dude.
Remembering David Hussman [04:28]
Joel Tosi: Yes.
Dion Stewart: Yes.
Shane Hastie: An incredible man. We’ve lost an absolute genius and guy. Tell us a little bit more about David.
Joel Tosi: Oh man. I think it’s easy to tell stuff about David mostly in stories. But when I first met David, he came into the Mercantile Exchange. This had to be the first or second day he had ever been in the Mercantile Exchange. So again, Chicago, trading systems, big, all of these. Our problems are the most complex in the world, this kind of views in the world. And David sat down and he is… I’m there and we’re sitting with some executive leadership, and David just very calmly said, “I think we can do better on testing.” He gave some examples and the director of QA at the time stood up, started screaming immediately at David shaking the table, and David just leans back, puts his hands in his hair, and he goes, “I’m sorry if you feel that way, dude, I’m just telling you what I see.” And David just gave him an example. And you could see the guy get upset and then he just kind of sat back and everybody immediately listened to David because David didn’t react. He didn’t react to the emotion, he just talked to the data.
That was one of the beautiful things about David, was he would just get to the essence of the problems just very succinctly in a kind way. He could have came at this gentleman harsh and he didn’t. It was just, “Look, here’s where we’re at. I want to help, but we have to see eye to eye on this.” And just the way he handled the situations was amazing. There was plenty of other stories, and I’ll give Dion a minute here, where David loved music. And so there was times he’d call us up in the middle of the night and he would compare something to Duran Duran or Depeche Mode all the time. He would talk about teams and, “They’re kind of like Duran Duran.” And he’d have all these analogies. Just the way he saw things was so beautiful and always challenging the way we would approach problems. I don’t know. Dion probably got more stories too. I want to give him an opportunity to share.
Dion Stewart: Yeah, I think, look, we could probably do a full 40 minutes on David, but the thing that immediately comes to mind is David was both very pragmatic. Whatever the complete opposite of dogmatic is, that was David. I think David understood the essence of agility, real agility. And the other thing that kind of goes along with Joel’s point is David didn’t really suffer fools at all. He wasn’t critical. He wasn’t mean to people, but he had a way of sort of cutting through any BS. His music background I think is important as well. That’s one of the things he and I bonded on. My undergrads actually in music and I started off wanting to be a musician. I’m sure many people who listen to the podcast are going, “Yeah, me too.” There’s some affinity, meaning playing music and programming. I think there’s something in the way musician’s brains are wired that actually lends itself well to programming or maybe the way our brains become wired by learning an instrument and learning how to play music.
Anyway, David was in this heavy metal band in the ’80s. They made it all the way to Abbey Road, recording an album. They had videos on Headbanger’s Ball on MTV. He was also Prince’s Guitar Tech for a while when he lived in Minneapolis. The reason I bring all of that up is David really understood the value and sort of the necessity of building communities. So he was really instrumental in building a community in Minneapolis of people who really cared about delivering quality products, digital products. And then even within all the organizations that I coached at with him, a lot of the discussion was around how do we build community within this organization? Yeah, we’re working sort of on a team by team basis when we first go in as well as with leadership and stakeholders, but really we’re trying to foster a community here.
And I think that’s probably the biggest hit to not only the Twin Cities community after we lost him, but a lot of the organizations that he worked with. Before he got sick, he was starting to really try to build up and foster a community around chaos engineering. He saw that as being sort of this next wave of interest or a place to build a community that was really going to take our industry to the next level. There was an event in Minneapolis, Norah Jones spoke at it. I think Casey Rosenthal. I’m trying to remember.
Joel Tosi: Kent Beck was there too.
Dion Stewart: Yeah, Kent was there. Kent didn’t speak. Kent was just interested, right?
Joel Tosi: Yeah. Yeah.
Dion Stewart: And David, now that you’ve reminded me that Kent was there, Joel, David made a comment that he was at some of the very early XP conferences. I think one of the first ones was over in Sicily, and he talked about the community again and the vibe and the willingness to share ideas and experiment among the people in that group. He said that this chaos community that was just starting was the first sort of community that reminded him of that experience and felt like it had the same energy and that it could really become this thing that, again, changed our industry for the better. I think chaos engineering is moving along. It’s certainly not growing in the ways I think David anticipated or hoped. It’s not surprising because it’s one of those things that’s hard and our industry tends to adopt the easy stuff.
Shane Hastie: Thank you. Yeah, just an opportunity to remember somebody who really has had a huge influence on very many of us, and that Dojo, that learning, his generosity in building community, inviting people in.
So that does lead me to Coaching for Learning. So you are technologists, you are technical coaches, you are helping people get better. Now you’ve written it down in a book, so what’s there that can be written about?
Coaching for Learning [10:30]
Joel Tosi: That’s a great question. So as I’m sure some of your listeners could attest to, as well as Shane, some of the ideas around coaching for learning are difficult to codify. Coaching to a process is more how do you follow a playbook? How do you follow a recipe? What are the things you tell people to do. When you’re coaching technologists for learning and how to be aware, it’s definitely more difficult to codify. In the book, we try to go through principles as well as why these principles are important, why the techniques are important, and then we try to give examples to help coaches think about when there are trying to help teams learn what to look for and how to approach it.
So some examples, and I had this conversation this morning with a technical coach that’s trying to help teams learn, we were talking about the hard thing for technologists is to want to go right to the answer. And especially as coaches, we wanted to say, “Here’s the answer, let’s go do this.” And I see a lot of technical coaches struggle with that balance versus, “Let’s capture the problem. Let’s capture the impact the problem is having, but let’s also be open to the ideas that there are potentially multiple ways of solving this problem.” And if we only explore one, but not only are we robbing ourselves of the opportunities of others, it’s really hard for us to say this is the right answer because we can’t say what the drawbacks are. And so when we’re thinking about how to codify this, especially in the book, we’re trying to just give perspective and principles around what you could do and should be thinking about.
Dion Stewart: The only thing I would add at a high level without digging into the weeds on principles and roles that we view coaches should have essential roles, I would say that Joel and I were doing a lot of coaching prior to this Dojo model. And as much as we were trying to help people learn how to have better products, higher quality, more effective ways of delivering, the emphasis was always on delivering, right? So it’s like you’re going to come in, you’re going to do the coaching, and then you’re going to help this team deliver the product. And it seemed like many times there’d be moments where we’d want to take the learning a little bit further and there wasn’t time because we had to get onto the next story or the next sprint and the next increment.
One of the things that Target did that I can’t give them enough credit, it’s amazing that an organization who was sort of experiencing some problems at that time with their technology stacks, that they invested in learning as much as they did and they created this space called Dojo, which we were around at the beginning of and sort of co-created with them, helped them create it. But the credit to them, their leadership and their stakeholders, for saying that, “We’re going to invest in our people. We’re going to invest in developing their capabilities. We know we’re going to take a hit in the short term in terms of productivity, for lack of a better word, or output.”
Making time to learn while delivering [13:18]
One of the principles for coaching for learning is for a time box period of time, the emphasis is on learning over delivery. So delivery takes a backseat that really shows up in cases where we might actually complete something, but maybe there was some differing of opinion on what the best technical solution might’ve been, in which case we’ll say, “Okay, now let’s go build it the other way and then we’ll have two real working solutions and we can have this discussion.” That kind of thing typically wouldn’t happen on a normal coaching engagement prior to this Dojo model, which we’ve been doing for a while now,
Shane Hastie: Tell us about the Dojo model. What’s special about it? I’m guessing it comes from martial arts just because it’s called a dojo, but what does it really mean? And if I think of one of our listeners, somebody who is in a senior technical position wanting to support others, what do they need to know?
The Dojo Model [14:14]
Joel Tosi: Conceptually, it’s learning in the flow of your work. That might sound kind of fuzzy or nebulous, but we’re learning new techniques and we’re focusing on learning while we’re building our product. And so, why that’s important, prior to doing a lot of this type of coaching, Dion and I, we taught two-day courses. We’re going to teach you TDD, we’re going to teach you at DevOps, we’re going to teach you CI. We’re going to teach you all these things. And everybody did great in all of the classes, not because Dion and I are great, but because, look, in controlled environments without the constraints of your organization, learning new techniques are easy. Without legacy code, writing that first test is easy, right? Without learning how to refactor and look for seams and look for ways for decoupling, these techniques are easy.
So the Dojo fundamentally is about learning new techniques with your code base, with your product, with all the challenges it has with all the constraints through your organization. “You want to learn how to do test driven development? Cool. Let’s start with your code base. What’s the simplest test we could do? Do we need to refactor something to get there? Let’s do the refactoring. Let’s try the test a couple different ways. What’s hard about that test?” And then we pause and we talk with the team, “What was hard about that experience? What do we want to try next? What ideas do we have to make it easier next time?”
And so it’s about getting in this way of learning and the way of approaching your products that’s continuously looking at how do we make it easier? What techniques could we learn that we want to try, but in the context of our actual work? If we want to learn how to do automated deployments, we’ll do it a piece at a time, but it’s got to be our deployments and our constraints in our world. Otherwise, the learning isn’t as sticky. So a Dojo is the team learning together within their constraints.
Dion Stewart: Just filling in some of the backdrop for Shane and to answer his questions, yes, it absolutely is a martial arts term. So the story behind Target’s Dojo, and at a certain point in time we had visibility to 50 different companies that were doing these, but let me go back to Target. I think it was 2015, a guy named Jason Walker, a really good technologist who was working at Target at the time, attended a conference and I think it was Adam Jacob, the Chef CEO, gave a talk on Developing DevOps Kung fu. I don’t remember the exact title of his talk. It’s out on the web. You can find it. But the metaphor or the analogy that Adam was making was that this isn’t something you just go to a two-day workshop and suddenly you absorbed, as Joel was sort of alluding to. This takes practice and repetition. And like studying a martial art, you don’t just go learn the form of a particular martial art or the moves. You have to go back and practice and spar and get feedback, and this is something that takes a long time.
So Jason came back to Target. They were talking about doing something to help teams get better initially at DevOps. The other sort of funny little anecdote is I guess there was some debate internally whether or not they were going to call this immersive learning place the Dojo or the sheep dipping farm, because sheep dipping was a term that Nathan Harvey and other people were using it for DevOps, right? I’m personally glad they went with Dojo. Dojo is a Japanese word. It was used for martial arts studios or is used for martial arts studios, particularly Aikido. It’s also used for meditation halls, although Zendo is probably more common than Dojo.
One thing I want to say right now while we’re talking about this, the question of whether or not using the word Dojo, whether that’s cultural appropriation or not, has come up several times. Joel and I are pretty sensitive to that. We don’t go beyond using the word, so we don’t use any symbols of torii gates or anything like that. We don’t use other words associated with Dojo. We’re certainly not going to create any stickers like, “You’re a sensei now” kind of thing. We’ve had some of our clients elect to call their dojo something else. At American Airlines, it was The Hangar. What was John Deere’s called, Joel?
Joel Tosi: The Combine Store
Dion Stewart : I think Stellantis, Fiat Chrysler was fast track, if I remember correctly.
Joel Tosi: Flywheel.
Dion Stewart: Flywheel. Flywheel. Thank you.
Joel Tosi: Yeah.
Dion Stewart: Yeah. So I just want to call that out for listeners in case anyone is starting to feel a little tingle of irritation. Joel and I have even talked about renaming Dojo and coat it to something different. It’s a possibility in the future. The other thing I’ll say about it is there is no English word equivalent, and it literally means place of the way, which is one of the reasons it’s a little bit hard for us to sort of give it up because it is so unique and because there isn’t really an English word equivalent.
At Target, there actually was a place, so they carved out part of their campus and teams would go into that space for six weeks at a time. I think there was something really powerful about even if you were just on the floor above in the same building normally about moving down into this different space where other teams were also focused on learning over delivery for a period of time and there were a lot of coaches there working with your team, and even if they weren’t working with your team, you could grab them if one of them had a specialty and one technology or another, there was just something really powerful about that space that I think is aligned with what a real Aikido dojo is.
Shane Hastie: You mentioned that there are some key principles and you touched on one. Tell us a few more.
Key principles of this approach to learning [19:51]
Dion Stewart: I think we’ve actually touched on a few of them just sort of in passing without necessarily calling them out. So we definitely touched on learning over delivery for a period of time. Joel mentioned it’s always doing your own real world work. So it’s learning in the context of doing your own real world work. It’s team learning instead of individual learning. So one of the problems that I’ve seen over and over in my own past with some of the two-day workshops that I’ve taught is organizations will send one, maybe two team members, to training with the instruction that, “Not only do you need to learn this, but you need to come back and teach the rest of the team,” right?
There are a few examples that I can refer back to where people came in and took a two-day test driven development course from me. When they went back, they tried to teach the rest of their team test-driven development. They couldn’t get it to stick. And as a result, if not everyone on the team is practicing it, but it’s a shared code base, you’re not going to end up with automated test suite for your unit tests. So it’s full team learning. We rely on, I’ll call it ensemble programming, right? Some people might know it as mob programming. We’re moving away from that term. Emily Bache’s really prodded us to move away from that term. She’s a great technical coach if people are unfamiliar with her, but she pointed out in Sweden, mobbing means bullying. So that’s not the connotation we want to have for collaborative teamwork,.
But I think there’s something really powerful about learning together as a group. It requires some vulnerability, but I think we can safely say that we’ve seen many times where junior developers realize that senior developers don’t know as much as they thought they did, or maybe another way of putting it is they don’t know everything. At the same time, we’ve seen less experienced engineers ask really amazingly pointed questions at just the right time that make some of the more experienced people stop dead in their tracks and say, “That’s a really interesting question. We should work through that.”
Another principle, and how this sort of stacks up against traditional training is, we try to make the learning as holistic as possible and span multiple practices. Another way of saying this is if you think about the development process as being your product development value stream, we’re trying to address as much of the value stream as possible. So Target started with DevOps. They eventually did the shift left thing where they started getting into, “Okay, well what happens before code commit and what are things that we can improve upon there, including their agile processes or their lean processes?”
And then we extended all the way back into product discovery. And what we found is if you go back to DevOps, the light bulb for engineers who were new to DevOps, really seeing the power of DevOps came when they made the link that, “Hey, if I have this product idea and I can get a very bare bones implementation of it out to a subset of our users, maybe A/B testing, and I’m able to do that quickly because of my DevOps pipeline and my other practices at the right end of the value stream, that’s where the value of DevOps really comes in.” It’s this really short feedback time and being able to test your product ideas out.
Yeah, there’s a ton of value in automating infrastructure and removing air from automation that comes when humans are doing deployments at 3:00 in the morning on Friday nights and that kind of thing. All that’s good, but what we found is when you really connect a lot of these ideas across the entire value stream, that’s really very powerful. It goes back to one of the early agile principles as well about not delivering things you don’t need. It’s the principle of delivering sort of essentials and how do we figure out what’s essential? Okay, some of the other principles, there are coaches there the entire time. So you’re getting feedback.
Joel and I like to say we don’t have a content problem in the world today, right? If you look at all the sites that are offering video content, books, all this material we can consume on technology, the problem is not the amount of content. I think the problem is we consume that content, it’s one way. We think we’re learning it and we start implementing it, but we don’t really have an opportunity for feedback for someone to say, “Yeah, you’re on the right track or not.”
A couple more principles. The other one is there’s time for repetition. So we’ve talked about six weeks being a typical duration for a lot of these dojos quite a bit. The idea there is, again, this isn’t something you’re just going to learn in two days and then hopefully it becomes part of the way you work. By having this six week time period where you’re focused on learning over delivery, we found that, just sort of through experimentation, was a sufficient length of time for ways of working to change and actually stick and stay with the team.
The last principle is we want to ensure learner safety, which I’m sure is of interest to your audience. I’m sure many of them are already familiar with this principle, but the basic idea there is that Dojo has to be a safe place to learn. So if we try an idea out as an experiment because we think we’re going to learn from it, if it leads to nothing, so we think we’re going to write some code, but we realize, “Boy, this was a rabbit hole and we got to throw the code away and start over,” one of the questions we have for people who want to do this dojo model is, “What happens then?” Is the team or is someone going to start griping that they just spent days or a week trying out some new technique that didn’t pan out, that didn’t lead to fruition?
So that’s the seventh principle. That Dojo has to be a place that’s safe for people to learn, both kind of within the team, showing vulnerability to each other, and kind of admitting you don’t know certain things as well as outside the team with stakeholders and other people who are interested in the performance of the team long term.
Shane Hastie: I can certainly see those principles and how they weave together. The other thing that you did mention was there are some essential roles that need to be present. Let’s explore that.
Joel Tosi: When we’re thinking about roles, we’re thinking about the coaching hats. What book was that from?
Dion Stewart: The Silsbee?
Joel Tosi: Silsbee? Yeah, there you go.
Essential Roles [26:29]
Dion Stewart: So Doug Silsbee wrote Presence-Based Coaching, a couple books. That’s one of them. And I believe that’s the book where he had seven roles for a coach. We kind of looked at that and modeled our approach on that. There’s overlap. We didn’t copy his roles exactly, we tweaked them a bit. That was the inspiration for ours.
Joel Tosi: And so obviously one role is a teacher. If you’re coaching for learning, you have to be able to teach. So when we’re working with teams, sometimes teams aren’t familiar with the new technique or they haven’t tried enough. So by all means at a very critical role is the ability to slow down and teach a new technique for teams. Another important one is we call it like a mirror. A nice role for a coach is this idea of a mirror. And so what that means in practice is teams are used to working the way they’ve been working and they might not be thinking about what’s actually happening. And so a very important role is being this mirror and taking a pause and playing back to the team. “Are we all aware of just what happened?”
To give you an example of that, I was working with a team. An engineer came in and said, “We have this defect. I have an idea, and here’s my proposed solution to this defect.” Then he walks through the team in about five minutes and he asks everybody, “What do you think?” And they all said, “Yes, that seems like the right idea. That’s the best implementation.” I go, “Okay.” I go, “Can I pause for a second here with the team?” And they go, “Sure, what’s up?” I say, You all agreed it’s the right implementation and you all said it’s the best implementation. I’m not disagreeing on that. What do you all mean right now by best?” And so we talked about it and I said, “Share with your peers what does best implementation mean to you.” Seven engineers, seven different answers.
One person said, “It’s solved. If it’s solved, it’s the best answer. I want to get to the other items.” Another person said, “It looks like it’s easy to implement.” So I had, “It’s done.” I had, “It’s easy.” Another person said, “I think I know how to test it.” Okay, so it’s testable. Another person said… I just don’t want to talk about it. You get where we’re going here. So this idea of playing back to the team, are we talking across each other or are we building dialogue together? It could be something like that. It could be playing back to the team, “Our deployments are failing nine out of 10 times. We’re getting them done, but let’s pause and say, are we all seeing the same things? Should we do something about it?” So being this mirror.
Sometimes we also talk about of course being the evangelist for the teams, being the champion. It might be hard to believe, Shane, but some problems are outside the team. So sometimes we have to be the champion. We have to say, “Hey, we’re in this. We’re here for you. We’re in this for you. And we’re also want to talk upwards and outwards around why this is hard for teams.” And so we want to be the champion and the evangelist for the teams. Dion, I know I’m missing four more there.
Dion Stewart: I don’t know if we need to rattle through every single one of them, but one I do want to call attention to and one thing I’ll point out, we don’t have facilitator as one of the roles. Nothing against people who are highly skilled at facilitation, but we think that’s a role that’s been overly stressed in the agile space over the last 20 years. And it sort of goes hand in hand with Scrum, which I’m actually a fan of Scrum as long as you’re coupling it with technical practices, which is also the way that I was taught Scrum by Ken Schwaber somewhere around 2003. He was adamant that if you were going to apply Scrum to software development, because it’s a project management framework, not a software development methodology, if you’re going to apply it to software development, you had to do the technical practices from XP. Too much of our industry has leaned towards, “We’re going to have someone come in and teach you Scrum and facilitate the Scrum ceremonies.”
So this leads me to what might be contentious. To a certain extent, Joel and I say, you have to be a practitioner if you’re going to be an effective coach for learning. Now, does that mean that every coach has to be a programmer or technical? Not necessarily. But if you are not and the team is trying to learn technical skills, you have to pair up with another coach. So it was quite common at Target for teams to have two coaches. One would be sort of the process, the agile lean coach, and oftentimes those people would learn enough product discovery practices and develop enough skill in that that they could introduce those practices to engineering teams. So sort of an agile product coach, if you will. The hardcore product coaches are cringing right now, but I’ll come back to that. So an agile product coach as well as a technical coach, someone who’s really heads down in development, current with technology.
The other thing that was really interesting for me to observe at Target was many of their technical coaches would cycle in and out of a coaching role. So it wasn’t necessarily a long-term career move for them. They would come work with teams in the Dojo for six months, maybe nine months, and then they would go back to being a contributor on a team or maybe a couple teams as a developer, an engineer, an architect, whatever their role was. But the point is, and we firmly believe this, you cannot coach something unless you are a practitioner yourself. I think that’s one of the reasons we’re seeing kind of a backlash against agile coaching these days. Organizations have spent a lot of money on agile transformations. They’ve hired all these, in theory, agile coaches that are going to help their teams deliver better. But at the end of the day, the coaches really only know the process practices. And if anything, they’re more facilitators than they are coaches.
Old guy rant warning here, I mentioned, I started kind of coaching in the aughts. At that point in time, I didn’t even call myself a coach. I was extremely hesitant, because to me, coaches were people like Michael Feathers and Kent Beck and Rebecca Wirfs-Brock and these people who had vast experience developing software and systems. Something happened at a certain point in time. I mean, I went to one event, Shane, where it was a partner event for one of the tool vendors, one of the agile project management tool vendors, and they had just released a new version of their software, so they wanted partners to come and learn about it so when they’re working with their clients, they know it.
I was in a room with about 25 people, about 20 of them were all from one consulting firm, which we’ll go unnamed. But about 15 of those 20 people when we were introducing ourselves said something to the effect of, “I graduated from university in the spring. I got hired as a business analyst. I just finished a two day yada yada yada certification course, and now I’m a coach.” And I was just kind of both horrified and in shock. But I think we’ve sort of done this to ourselves, if you will, as an industry. I know there are groups, I see agile and other groups that are trying to put meaning behind the term coach and make it so that when organizations are hiring coaches, they know they’re getting a person of skill and value. But it’s been a problem and I think it’s why we’re kind of where we’re at today.
Shane Hastie: I have to say I’m with you there. And my work among others on the agile coaching ethics and one of the key points of that is do not say that you have a competency that you don’t. Gentlemen, thank you very much. Really interesting stuff. If people want to, first of all, find the book, just to remind us, what’s it called and where can they get it?
Joel Tosi: The book’s called Coaching for Learning: The Art and Practice available on Amazon.
Shane Hastie: And if people want to continue the conversation with yourselves, where do they find you?
Dion Stewart: dojoandco.com or we’re both on LinkedIn. A lot of people reach out to us via LinkedIn.
Shane Hastie: Thank you so much.
Joel Tosi: Thanks, Shane.
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Investors often turn to recommendations made by Wall Street analysts before making a Buy, Sell, or Hold decision about a stock. While media reports about rating changes by these brokerage-firm employed (or sell-side) analysts often affect a stock’s price, do they really matter?
Before we discuss the reliability of brokerage recommendations and how to use them to your advantage, let’s see what these Wall Street heavyweights think about MongoDB (MDB – Free Report) .
MongoDB currently has an average brokerage recommendation (ABR) of 1.44, on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations (Buy, Hold, Sell, etc.) made by 25 brokerage firms. An ABR of 1.44 approximates between Strong Buy and Buy.
Of the 25 recommendations that derive the current ABR, 19 are Strong Buy and three are Buy. Strong Buy and Buy respectively account for 76% and 12% of all recommendations.
Brokerage Recommendation Trends for MDB
Check price target & stock forecast for MongoDB here>>>
The ABR suggests buying MongoDB, but making an investment decision solely on the basis of this information might not be a good idea. According to several studies, brokerage recommendations have little to no success guiding investors to choose stocks with the most potential for price appreciation.
Are you wondering why? The vested interest of brokerage firms in a stock they cover often results in a strong positive bias of their analysts in rating it. Our research shows that for every “Strong Sell” recommendation, brokerage firms assign five “Strong Buy” recommendations.
This means that the interests of these institutions are not always aligned with those of retail investors, giving little insight into the direction of a stock’s future price movement. It would therefore be best to use this information to validate your own analysis or a tool that has proven to be highly effective at predicting stock price movements.
Zacks Rank, our proprietary stock rating tool with an impressive externally audited track record, categorizes stocks into five groups, ranging from Zacks Rank #1 (Strong Buy) to Zacks Rank #5 (Strong Sell), and is an effective indicator of a stock’s price performance in the near future. Therefore, using the ABR to validate the Zacks Rank could be an efficient way of making a profitable investment decision.
ABR Should Not Be Confused With Zacks Rank
In spite of the fact that Zacks Rank and ABR both appear on a scale from 1 to 5, they are two completely different measures.
The ABR is calculated solely based on brokerage recommendations and is typically displayed with decimals (example: 1.28). In contrast, the Zacks Rank is a quantitative model allowing investors to harness the power of earnings estimate revisions. It is displayed in whole numbers — 1 to 5.
It has been and continues to be the case that analysts employed by brokerage firms are overly optimistic with their recommendations. Because of their employers’ vested interests, these analysts issue more favorable ratings than their research would support, misguiding investors far more often than helping them.
On the other hand, earnings estimate revisions are at the core of the Zacks Rank. And empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements.
In addition, the different Zacks Rank grades are applied proportionately to all stocks for which brokerage analysts provide current-year earnings estimates. In other words, this tool always maintains a balance among its five ranks.
Another key difference between the ABR and Zacks Rank is freshness. The ABR is not necessarily up-to-date when you look at it. But, since brokerage analysts keep revising their earnings estimates to account for a company’s changing business trends, and their actions get reflected in the Zacks Rank quickly enough, it is always timely in indicating future price movements.
Is MDB Worth Investing In?
Looking at the earnings estimate revisions for MongoDB, the Zacks Consensus Estimate for the current year has remained unchanged over the past month at $2.34.
Analysts’ steady views regarding the company’s earnings prospects, as indicated by an unchanged consensus estimate, could be a legitimate reason for the stock to perform in line with the broader market in the near term.
The size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, has resulted in a Zacks Rank #3 (Hold) for MongoDB. You can see the complete list of today’s Zacks Rank #1 (Strong Buy) stocks here >>>>
It may therefore be prudent to be a little cautious with the Buy-equivalent ABR for MongoDB.
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