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Online database Database Easy access locally using your local network or the internet. An online database provides Software as a Service (SaaS) in a web browser because it is hosted on a website through a cloud model instead of storing data directly on the desktop and the storage connected to it. These web-based applications may be free or may require payment, typically as monthly and annual subscriptions. You pay for what you use. Therefore, the amount of server space required can be changed accordingly.
Everything is kept in the cloud, eliminating the hassle of installing the entire software. Information is always accessible from almost any device. Everything is stored in the cloud, so you don’t have to be tied to just one computer. Technically, data can be retrieved from any compatible device as long as access is granted. Such databases also come with in-house technical support, which provides services 24 hours a day, 7 days a week.Some examples of such databases Oracle databaseNotorious as IBM Db2 Amazon DynamoDB..
What is Redis?
Redis, also known as the Remote Dictionary Server, is an ultra-fast, open source, in-memory key-value data store created for use as a database, cache manager, message broker, and queue. All Redis data resides in memory and is inconsistent with other databases that store data on disks or SSDs. In-memory data stores such as Redis avoid response time delays and access microseconds of data because they do not need to access disks. This allows Redis to support mapped key-value-based strings to store and retrieve data in parallel with the data models supported by traditional types of databases, while others such as lists and sets. Means that it also supports complex data structures in.
Key features of Redis include versatile data structures, high availability, geospace, Lua scripts, transaction management, on-disk persistence, cluster support, and easy to teach in real-time, Internet-scale apps. I will. Redis is a type of database commonly referred to as NoSQL or Non-relational. Therefore, Redis has no table or database definition method for associating Redis data with other data. Ultimately needed because Redis replaces common relational databases and other primarily on-disk databases, avoiding unnecessary temporary data writes and eliminating the need to scan and delete entire temporary data. Performance is improved.
How does Redis work?
Redis works by mapping keys to values using some kind of predefined data model. It also divides the data into different parts using a method called sharding. Splits the data based on the ID embedded in the key, the hash of the key, or a combination of the two. Partitioning data allows you to store and fetch data from multiple machines, allowing you to linearly scale the performance of certain problematic domains.
Due to its in-memory design, Redis works very well in the most uncertain situations, but if you need Redis to handle more read queries than a single Redis server can handle. there is. Therefore, Redis supports master / slave server instance replication to support read performance and faster processing of server failures where Redis is running.
Redis supports master / slave server instance replication. In this replication, the slave connects to the master and receives an initial copy of the entire database. Therefore, when the master writes data, it is also sent to all connected slaves and updated in real time. Continuously updated slaves allow clients to connect to any slave to read data in the event of a crash or connectivity issue with the master server. It can also be combined with another database to reduce the load.
Supported data types
Some of the data types supported by Redis are:
- String: You can manipulate whole or part of the string to increment / decrement integers and floating point numbers.
- List: You can push or pop items from both ends, read individual or multiple items, and use values to find and delete items.
- Sets and Sorted Sets: Allows you to add, fetch, delete, check membership, intersect, unions and variances for individual and random items
- Hash: Add, fetch, remove items, or fetch the entire hash
Which languages does Redis support?
Redis simplifies your code by reducing the number of lines of code to store, access, and use the data in your application. With multiple supported data structures, you can store data in a data store with just a few lines of code and come with options for manipulating and manipulating the data. Developers using Redis have access to over 100 open source clients.
The supported languages are:
- C, C ++ and C #
- More when you go.
Redis High Availability and Scalability
Redis provides primary replication of the architecture in a single node primary or cluster topology. This allows users to build highly available solutions and maintain consistent performance and reliability. In addition, there are many options available for adjusting the cluster size, which can be scaled up or scaled in or out. This gives users the flexibility to grow their cluster according to their needs and uses.
Caching with Redis
Redis is a great option for implementing highly available in-memory caches to reduce data access latency and increase throughput. This is because Redis can deliver frequently requested data items in milliseconds. Caching is the process of storing a similar copy of a file in a temporary storage location for immediate access. Technically, a cache is a temporary storage location for a copy of a file or data, but the term is often used in connection with Internet technology. Database queries allow you to cache caches, persistent session caches, web page caches, and frequently requested objects such as images, files, and metadata. Therefore, these are common examples of caching with Redis. With the ability to specify how long data is retained and what data to delete first, Redis enables a set of intelligent caching patterns.
Expiration and deletion of data using Redis
Redis data structures can be tagged as Time to Live and set in seconds accordingly. It is then deleted from the database. You can choose from a set of configurable eviction policies. Time to Live allows you to create a hierarchical hierarchy of memory objects because you can consider non-persistent marked data before other data that does not have Time to Live. It makes much more sense to delete the least recently used or least used objects.
Redis geospatial features
Redis contains a wealth of geospatial index data structures and commands to use. These built-in memory data structures and operators help you manage real-time geospatial data on a large scale and at high speed. For example, latitude and longitude coordinates are saved, allowing users to calculate distances between objects and query objects within a specific radius of a point. Implementing these commands returns values in multiple formats, such as feet and kilometers.
Redis speed allows you to update these data points quickly. Therefore, it can be implemented in ride-sharing applications to connect with nearby drivers and provide real-time updates as drivers move when used properly.
Some Redis use cases
Modern database applications require machine learning to quickly process large amounts of fast-moving data, making Redis a potential savior for such fast-moving operations. Redis is ideal for these use cases because it allows you to process, build, train, and deploy machine learning models through faster processing. Redis can also be used with steam solutions such as Apache Kafka and Amazon Kinesis to capture and process real-time data with low latency. It can also be used for social media analytics, ad targeting, personalization and IoT.
Use of Redis
For demonstration purposes, I implemented the following code on the Redis website via the tutorial UI. You can implement the following code on your system by installing the Redis-CLI.You can download the CLI from the link Here..
As an example, first set the server name to “victor” and the key to “Hello World”.
If the key is set, the next output is[OK]Will be obtained as.
Get the key
To get the set key, use the following command:
> GET victor
You can use the following command to delete the key you created.
(integer) 1 #key got deleted
Mutual verification of results
Therefore, you can be sure that the key has been permanently deleted.
Setting a key with a lifetime
You can also set a key with an expiration date. The time is set in seconds and the key is removed from the server after the set time.
> SETEX victor 40 "I said, Hello World!" #key set with 40 seconds as time limit OK
Confirmation of duration
You can also check the remaining time from the set time to the expiration.
Rename the key
You can rename the key using the following command:
> RENAME victor bar #renaming victor as bar OK
Flash the key
Flash everything saved so far.
OK #just got flushed
Through this article, I tried to understand what Redis is and what Redis can do. I also investigated its use case and ran basic Redis database commands to try to see its functionality. Redis is optimized to provide high-performance and efficient reads and writes. Therefore, it is advisable to investigate the Redis database further and implement it for its vast functionality.
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Turns out the recent story about the personal news reader NewsBlur being down for several hours last week following a data exposure has a happy ending: the owner retained an original copy of the database that was compromised and restored the service in 10 hours.
The actual database exposure was caused by a persistent problem with Docker, an issue that’s been fairly well-known in the Linux community for several years. Evidently, when sys admins use Docker to containerize a database on a Linux server, Docker inserts an “allow rule” into iptables, opening up the database to the public internet. This requires sys admins to reconfigure the uncomplicated firewall (UFW) configuration file on the server and insert new rules for Docker.
In the NewsBlur case, the database (about 250 gigabytes) was compromised and ransomed while the RSS reader was using Docker to containerize a MongoDB. NewsBlur founder Samuel Clay said in a blog post that the hacker was able to copy the database and delete the original in about three hours.
Clay used some best practices security pros should consider: right before he transitioned to Docker, he shut down the original primary MongoDB cluster, which was untouched during the attack. Once he was aware of the issue, Clay then took the snapshot of the original MongoDB, restored the database, patched the Docker flaw, and got the service up and running.
It’s examples like the NewsBlur case that demonstrate why container security has become one of the fastest growing areas in cybersecurity, said Ray Kelly, principal security engineer at WhiteHat Security. Kelly said companies are moving at a frantic pace to move to containerized architectures to help with scalability and redundancy – and they often don’t consider the security implications.
“Each container is essentially its own mini OS and needs to be vetted for security vulnerabilities such as privileges/roles, application layer attacks and in this case network and firewall openings,” Kelly explained. “Ideally these tasks are done before going live. Unfortunately, security often gets placed in the back of the queue in favor of new features and fast deployments.”
Andrew Barratt, managing principal, solutions and investigations at Coalfire, added that as the architecture of our systems becomes more complex, with more automation, containerization, and virtualization, it’s vital to not make any assumptions about the security configurations.
“Active testing of these would have caught this early if done by an experienced adversary simulation or most likely even a more traditional architectural review,” Barratt said. “Sadly, the tables got dropped and the data was no more. At least in this instance, there was no need to pay the ransom.”
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Check out the companies that make headlines for noon trading.
WideOpenWest — US cable operators have seen a 13.4% rise in stock prices after announcing that they will sell five service areas in two separate transactions for a total of $ 1.8 billion to reduce debt. The transaction is expected to close in the second half of the year.
Bed bath & beyond — Retailer share has since surged 11.3% Report better sales than expected We improved our first-quarter results and raised our full-year outlook. Stocks are unusually high, suggesting that some of the rise may have been due to the return of Reddit traders who helped boost stocks earlier this year.
Virgin Galactic — Stocks have since fallen 2.1% Bank of America double downgrade shares Underperform from purchase. According to the company, Virgin Galactic’s soaring share price has already priced many of the final profits the company expects when it embarks on space travel. BofA also noted that the space sector continues to carry risks and volatility.
MongoDB — Database platform company shares fell 5.7% after announcing that they would sell 2.5 million Class A common stock and raise $ 889 million. MongoDB said it plans to use the proceeds of the sale for general corporate purposes.
Advanced Micro Devices — Semiconductor companies’ stock prices rose 4.9% after Bank of America repeatedly rated it as “convincing” and “undervalued.”
Constellation Brands — Spirits and beer maker shares have risen nearly 1.3% since the company’s quarterly report. According to Refinitiv, Constellation Brands reported adjusted quarterly earnings of $ 2.33 per share, consistent with Wall Street’s forecast. Its revenue was slightly higher than expected.
Las Vegas Sands — Casino and resort company stocks traded 2.96% higher after reports of Covid-related restrictions between Hong Kong and Macau, where the company owns and operates five properties, will be relaxed in July. I did. Travelers from Hong Kong to Macau are currently required to quarantine for 14 days upon arrival.
General Mills — Food producers reported a quarterly earnings of 91 cents per share, after which stock prices rose 1.5%, 6 cents above analysts’ estimates. The company also reported revenue of $ 4.52 billion, with an estimated $ 2.02 billion.
— CNBC’s Hannah Miao, Yun Li and Jesse Pound contributed to the report
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This is an excerpt from Chapter 15 of the book NoSQL for mere mortals Along Dan Sullivan, Independent database consultant and author. In this chapter, Sullivan looks at four major types of NoSQL databases: key-value, document, column family, and graph databases, and provides insights into the best application for each. He also explains the difference between relational database design and NoSQL database design, and the need for relational and NoSQL technology to coexist in many organizations.
In relational database design, the structure and relationships of entities drive the design, but in NoSQL database design it is not. Of course, we model entities and relationships, but performance is more important than maintaining a relational model.
The· Relational model Appeared for practical reasons. This is due to data anomalies and the difficulty of reusing existing databases for new applications. NoSQL databases have also emerged for practical reasons. Specifically, it cannot be scaled to meet the growing demand for high volume read and write operations.
Immediate integrity and in exchange for improved read and write performance ACID transaction (However, this is not always the case).
Throughout this book, Queries has driven the design of data models. This is true because the query explains how to use the data. Queries are also a good starting point for understanding how different NoSQL databases meet your needs. You also need to understand other factors, such as:
- Amount of reads and writes
- Tolerance for inconsistent data in replicas
- The nature of relationships between entities and how they affect query patterns
- Availability and disaster recovery requirements
- The need for data model flexibility
- Latency requirements
The following sections provide some sample use cases and some criteria for matching different NoSQL database models to different requirements.
Criteria for selecting a key-value database
Key-value databases are ideal for applications where small reads and writes are frequent in addition to a simple data model.Value stored in Key value The database can be a simple scalar value such as an integer or a Boolean value, but it can also be a structured data type such as a list or JSON structure.
Key-value databases usually have a simple query function that allows you to search for a value by key. Some key-value databases support search capabilities that provide some flexibility.Developers can implement range queries using tricks such as enumeration keys, but these databases typically have documents, column families, and Graph database..
Key-value databases are used in a wide range of applications, including:
- Cache data from a relational database for better performance
- Tracking temporary attributes of web applications such as shopping carts
- Mobile application configuration and storage of user data information
- Saving large objects such as images and audio files
Use cases and criteria for choosing a document database
The document database is designed with flexibility in mind. Document databases are a good choice if your application requires the ability to store various attributes with large amounts of data.For example, to represent a product Relational database, Modelers can use a table of common attributes and additional tables for each product subtype to store attributes that are used only in the product subtype. The document database can easily handle this situation.
The document database provides embedded documents that are useful in the following cases: Denormalized.. Instead of storing data in different tables, data that is frequently queried together is stored together in the same document.
In addition, the document database improves the ability to query key-value databases for indexing and the ability to filter documents based on attributes within the document.
Document database is probably The most popular NoSQL database For flexibility, performance and ease of use.
These databases are suitable for many use cases, including:
- Backend support for heavy read and write websites
- Data type management with variable attributes such as products
- Tracking variable types in metadata
- Applications that use JSON data structures
- Benefiting applications Denormalized By embedding the structure within the structure
Document database is Microsoft Azure Document Cloudant database..
Use cases and criteria for choosing a column family database
Column family databases are designed for large amounts of data, read and write performance, and high availability. Introduced by Google Bigtable To meet the needs of that service. Developed by Facebook Cassandra Back up your inbox search service.
These database management systems run in a cluster of multiple servers. If the data is small enough to run on a single server, the column family database can be larger than necessary. Instead, consider a document or key-value database.
Column family database Ideal for use in:
- Applications that need the ability to constantly write to the database
- Geographically distributed applications across multiple data centers
- Applications that can tolerate short-term replica inconsistencies
- Applications with dynamic fields
- Applications that can generate really large amounts of data, such as hundreds of terabytes
Google has demonstrated the functionality of Cassandra running Cassandra Google computing engine.. Deployed Google Engineer:
- 330 Google Compute Engine Virtual Machine
- 300 1TB persistent disk volume
- Debian Linux
- Datastax Cassandra 2.2
- Data was written to two nodes (quorum commit 2)
- Generate 3 billion records of 170 bytes each in 30 virtual machines
In this configuration, Cassandra clusters reached 1 million writes per second, with 95% completing in less than 23 ms. When one-third of the nodes were lost, one million writes were maintained, but the latency was higher.
You can use this kind of big data processing feature in several areas, such as:
- Security analysis using network traffic and log data mode
- Big science such as bioinformatics using genetic data and proteomics data
- Stock market analysis using trade data
- Web scale applications such as search
- Social network service
Key-value, document, and column family databases are ideal for a wide range of applications. However, graph databases are best suited for certain types of problems.
Use cases and criteria for choosing a graph database
Problem domains that are useful to represent as a network of connected entities are ideal for graph databases. One way to evaluate the usefulness of a graph database is to determine if an instance of an entity is related to other instances of the entity.
For example, two orders in an e-commerce application are probably not interrelated. They may be ordered by the same customer, but it is a shared attribute, not a connection.
Similarly, the composition of a game player and the state of the game have little to do with the composition of other game players. Such entities can be easily modeled using key-value, document, or relational databases.
Now consider the examples mentioned in the graph database description, such as highways connecting cities, proteins that interact with other proteins, and employees who work with other employees. In all of these cases, there is some type of connection, link, or direct relationship between the two instances of the entity.
These are the types of domains that have problems. Ideal for graph databases.. Other examples of these types of problem domains are:
- Network and IT infrastructure management
- ID and access management
- Business process management
- Product and service recommendations
- Social networking
From these examples, it’s clear that graph databases are a great database option when you need to model explicit relationships between entities and quickly traverse paths between entities.
Large graph processing, such as large social networks, may actually use column families. Database for storage And search. Graph operations are built on top of a database management system.The· Giant Graph databases and analytics platforms take this approach.
Key-values, documents, column families, and graph databases address different types of needs. Unlike relational databases, which essentially replaced their predecessors, these NoSQL databases are reciprocally and relationally because of the increasing need for different types of applications with requirements that conflict with different requirements. Continues to coexist with the database.
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The trading price of MongoDB Inc. (NASDAQ:MDB) floating lower at last check on Wednesday, June 30, closing at $366.42, -4.51% lower than its previous close.
Traders who pay close attention to intraday price movement should know that it has been fluctuating between $380.71 and $391.26. In examining the 52-week price action we see that the stock hit a 52-week high of $428.96 and a 52-week low of $186.27. Over the past month, the stock has gained 31.43% in value.
MongoDB Inc., whose market valuation is $24.06 billion at the time of this writing. Investors’ optimism about the company’s current quarter earnings report is understandable. Analysts have predicted the quarterly earnings per share to grow by -$0.39 per share this quarter, however they have predicted annual earnings per share of -$1.3 for 2022 and -$0.91 for 2023. It means analysts are expecting annual earnings per share growth of -31.30% this year and 30.00% next year.
Analysts have forecast the company to bring in revenue of $183.84 million for the current quarter, with the likely lows of $181.5 million and highs of $194.3 million. From the analysts’ viewpoint, the consensus estimate for the company’s annual revenue in 2022 is $785.42 million. The company’s revenue is forecast to grow by 33.00% over what it did in 2022.
A company’s earnings reviews provide a brief indication of a stock’s direction in the short term, where in the case of MongoDB Inc. No upward and no downward comments were posted in the last 7 days. On the technical side, indicators suggest MDB has a 100% Buy on average for the short term. According to the data of the stock’s medium term indicators, the stock is currently averaging as a Hold, while an average of long term indicators suggests that the stock is currently 100% Buy.
Here is the average analyst rating on the stock as represented by 1.00 to 5.00, with the extremes of 1.00 and 5.00 suggesting the stock should be considered as either strong buy or strong sell respectively. The number of analysts that have assigned MDB a recommendation rating is 17. Out of them, 4 rate it a Hold, while 12 recommend Buy, whereas 0 assign an Overweight rating. 0 analyst(s) have tagged MongoDB Inc. (MDB) as Underweight, while 1 advise Sell. Analysts have rated the stock Overweight, likely urging investors to take advantage of the opportunity to add to their holdings of the company’s shares.
A quick review shows that MDB’s price is currently 4.81% off the SMA20 and 18.19% off the SMA50. The RSI metric on the 14-day chart is currently showing 59.72, and weekly volatility stands at 2.93%. When measured over the past 30 days, the indicator reaches 4.19%. MongoDB Inc. (NASDAQ:MDB)’s beta value is currently sitting at 0.73, while the Average True Range indicator is currently displaying 13.06. With analysts defining $300.00-$450.00 as the low and high price targets, we arrive at a consensus price target of $379.67 for the trailing 12-month period. The current price is about 18.13% off the estimated low and -22.81% off the forecast high, based on this estimate. Investors will be thrilled if MDB’s share price rises to $387.00, which is the median consensus price. At that level, MDB’s share price would be -5.62% below current price.
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To see how MongoDB Inc. stock has been performing today in comparison to its peers in the industry, here are the numbers: MDB stock’s performance was -4.51% at last check in today’s session, and 74.08% in the past year, while Progress Software Corporation (PRGS) has been trading -0.88% in recent session and positioned 20.06% higher than it was a year ago. Another comparable company Pixelworks Inc. (PXLW) saw its stock trading -3.40% lower in today’s session but was up 9.97% in a year. MongoDB Inc. has a P/E ratio of 0, compared to Progress Software Corporation’s 27.20 and Pixelworks Inc.’s 0. Also during today’s trading, the S&P 500 Index has surged 0.08%, while the Dow Jones Industrial also saw a positive session, up 0.43% today.
An evaluation of the daily trading volume of MongoDB Inc. (NASDAQ:MDB) indicates that the 3-month average is 821.44K. However, this figure has increased over the past 10 days to an average of 0.63 million.
Currently, records show that 61.36 million of the company’s shares remain outstanding. The insiders hold 3.10% of outstanding shares, whereas institutions hold 86.60%. The stats also highlight that short interest as of Jun 14, 2021, stood at 5.82 million shares, resulting in a short ratio of 6.87 at that time. From this, we can conclude that short interest is 9.37% of the company’s total outstanding shares. It is noteworthy that short shares in June were up slightly from the previous month’s figure, which was 5.33 million. However, since the stock’s price has seen 6.87% year-to-date, investors’ interest is likely to be reignited due to its potential to move even higher.
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By Dhirendra Tripathi
Investing.com – MongoDB (NASDAQ:MDB) fell nearly 5% in Wednesday’s trading as the company increased the size of its equity offering by 200,000 shares to 2.5 million while pricing it at $365 apiece.
The shares slipped to trade around the level in the offering.
MongoDB estimates that the net proceeds from the sale of the shares will be approximately $889 million, after deducting underwriting discounts and commissions and estimated offering expenses.
The database platform provider plans to use the proceeds for general corporate purposes. The issue is expected to close Friday.
As per MongoDB’s prospectus, IDC has pegged the worldwide database software market at $73 billion this year and $119 billion in 2025.
Stocks making the biggest moves midday: Bed Bath & Beyond, Virgin Galactic, WideOpenWest and …
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Check out the companies making headlines in midday trading.
WideOpenWest — The U.S. cable operator saw its stock price increase 13.4% after it announced it will sell five of its service areas in two separate deals for a combined $1.8 billion in an effort to lower its debt. The transactions are expected to close in the second half of the year.
Bed Bath & Beyond — Shares of the retailer jumped 11.3% after reporting better-than-expected sales results for its fiscal first quarter and raised its full-year outlook. Volume in the stock was abnormally high, suggesting that part of the rise might be due to a return of Reddit traders that helped to boost shares earlier this year.
Virgin Galactic — Shares dropped 2.1% after Bank of America double-downgraded the stock to underperform from buy. The firm said that Virgin Galactic’s surging stock price has already priced in much of the eventual gains expected when the company launches space tourism. BofA also noted the space sector continues to carry risk and volatility.
MongoDB — Shares of the database platform company lost 5.7% after it said it would sell 2.5 million Class A common shares, seeking to raise $889 million. MongoDB said it plans to use the proceeds of the sale for general corporate purposes.
Advanced Micro Devices — The semiconductor company’s stock is up 4.9% after Bank of America reiterated its buy rating on it, calling the stock “compelling” and “underappreciated.”
Constellation Brands — Shares of the spirits and beer maker rose nearly 1.3% after the company’s quarterly report. Constellation Brands reported adjusted quarterly profit of $2.33 per share, matching Wall Street forecasts, according to Refinitiv. Its revenue came in slightly above estimates.
Las Vegas Sands — The casino and resort company’s stock traded 2.96% higher after reports came out saying Covid-related restrictions between Hong Kong and Macau, where the company owns and operates five properties, will loosen in July. Travelers from Hong Kong to Macau are currently required to quarantine for 14 days upon arrival.
General Mills — The food producer saw shares rise 1.5% after it reported quarterly earnings of 91 cents per share, beating analysts’ estimates by 6 cents. The company also reported $4.52 billion in revenue, on estimates of $2.02 billion.
— CNBC’s Hannah Miao, Yun Li and Jesse Pound contributed reporting
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Shares of database software company MongoDB (NASDAQ:MDB) are down 4.4% as of midday Wednesday, following the company’s decision to raise funds by selling newly issued stock.
As other organizations have of late, MongoDB is capitalizing on its stock’s recent gains by issuing new shares while prices are elevated. The company announced after Tuesday’s close it intends to sell 2.3 million new shares of its common stock, but revised that figure to 2.5 million late Tuesday evening. The offering price of $365 per share was less than Tuesday’s closing price of $383.71, offering a discount to new buyers. As of the end of January, 60.9 million shares of MongoDB common stock were outstanding.
Secondary stock offerings are nothing unusual, particularly in the current environment. Many companies’ stocks have soared on hopes for a firm economic recovery, even if the recent past’s fiscal results aren’t exactly impressive. As the adage goes, opportunity knocks but once. If corporations don’t cash in now, they may not be able to again — at least not this well — for a long while.
It’s not unfair to ask, however, if these dilutive fundraisers are truly necessary. MongoDB will use the proceeds from this sale for “general corporate purposes,” which ultimately means they will be used to generate business growth. The company was already on pace to grow its top line by 33% this year, though, and expand it another 30% next fiscal year. Without a clear reason to issue so many new shares (at a discount to the current market price, no less) investors are understandably protesting the deal — by selling already-issued stock.
Fortunately for all involved, MongoDB’s underlying database software story has proven to be consistently a compelling one, buoying the stock following any significant dips like today’s.
This article represents the opinion of the writer, who may disagree with the “official” recommendation position of a Motley Fool premium advisory service. We’re motley! Questioning an investing thesis — even one of our own — helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.
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Global NoSQL Software market analysis mainly introduces the changing market dynamics in terms of covering all details inside analysis and opinion, volume and value market share by players, by regions, by product type, by consumers and their price change details, cost/revenue structure. Additionally, the analysis of Market offers a detailed breakdown of key market growth drivers and limitation along with impact analysis of the same.
According to the report, the Transcriptome Sequencing market is projected to expand with XX% CAGR over the forecast period 2020-2025.
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In recent times, the coronavirus outbreak is peaking in some markets while its lingering impact continues to challenge others. Amid the uncertainties, companies are revising their budget for reopening and reinventing with full force but now they must consider the pandemic’s progression and its recurrence across the various geographies. Our deep dive analysis of this business sphere will not only help you chart a plan of action for recovery but will empower you in crafting strategies to remain profitable.
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- Covid-19 impact on remuneration scale of the industry.
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Transcriptome Sequencing market segments included in the report:
- Regional segmentation: North America, Europe, Asia-Pacific, South America, Middle East and Africa
- Country-level analysis.
- Total sales, revenue, and market share of each region.
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- Total RNA
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- The major players covered in Transcriptome Sequencing are:
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- Assessment of business centric aspects like commercialization rate, market concentration ratio, and popular marketing strategies.
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MongoDB, Inc. (NASDAQ: MDB) shares are trading lower on Wednesday after the company priced its upsized public offering of 2.5 million shares of common stock at $365 per share.
“MongoDB estimates that the net proceeds from the sale of the shares will be approximately $889.0 million,” according to the press release.
MongoDB is a document-oriented database with nearly 25,000 paying customers and well past 1.5 million free users. The company provides both licenses as well as subscriptions as a service for its NoSQL database.
MongoDB’s stock was trading about 4.5% lower at $366.38 at the time of publication. The stock has a 52-week high of $428.96 and a 52-week low of $186.27.
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