Month: June 2023

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June 22, 2023, 02:47 PM EDT

At MongoDB.local NYC Thursday the database company also launched a number of new AppDev capabilities designed to encourage developers to build their next-generation applications on the MongoDB Atlas cloud database.

MongoDB has unveiled a wave of new software products and capabilities for its MongoDB Atlas developer data platform, new offerings that the company said will help partners and customers build new classes of data-intensive applications.

The company, which is holding its MongoDB.local NYC developer conference in New York Thursday, also said its MongoDB Relational Migrator, for transforming and moving legacy applications to the cloud, is now generally available.

And artificial intelligence was high on the event’s agenda with the launch of the AI Innovators Program to help businesses and organizations build applications using generative AI technology.

[Related: MongoDB And Alibaba Cloud Extend Strategic Partnership By Four Years]

“Our mission is truly to enable or empower innovators to create, transform and disrupt industries by unleashing the power of software and data,” MongoDB CEO Dev Ittycheria said in his MongoDB.local NYC keynote. “We want developers to have the biggest impact they can [through] the applications that they’re building.”

Ittycheria said the average developer spends anywhere from 30 to 70 percent of their time working with data.

“When you think about impact and how can we impact developer productivity, then the obvious answer is, make it easy to work with data,” the CEO said. “And this has essentially been our Northstar as a company in terms of the products we’re building, the features we’re thinking about, the capabilities we’re introducing, everything is all about making it incredibly easy to work with data. And that started with our database. It was the first database designed by developers for developers and the focus was all about the developer experience.”

MongoDB’s NoSQL, document-oriented, high-scalability database is designed for running big data application workloads, making application developers a key constituency for the company. MongoDB Atlas is the company’s database-as-a-service built on the company’s database server.

“We think that in the years to come there’s going to be an explosion in the number of workloads,” said Andrew Davidson, MongoDB senior vice president of product, in a press briefing prior to the Thursday event.

“Essentially, we find ourselves in a software-defined economy. And a software-defined economy is a developer-defined economy,” Davidson continued. “Developers are making all this possible [and] choosing the technology, the databases, that are powering all of these applications. And new development technologies, ranging from generative AI to low- and no-code, will all democratize and accelerate this trend. There’s going to be more and more software, more and more workloads. Everything that we’re doing is in line with this.”

Artificial intelligence was a major component of the MongoDB.local NYC announcements.

“We see AI as a driver for enormous economic value in the form of new applications in every industry. We think MongoDB will be a preferred platform for all of these AI powered applications,” said Davidson, who called AI the next development paradigm. “AI will accelerate application modernization.”

“Generative AI is an accelerant to developers writing new applications. It’s just fast. The trend is pretty obvious that developers will use AI to code faster but also write applications that help businesses become more agile,” said Alan Chhabra, MongoDB executive VP of worldwide partners, in a pre-event interview with CRN. “As part of our general AI strategy, we want companies to build on MongoDB.”

He noted that the extensive alliances MongoDB has forged with the major cloud platform providers: Amazon Web Services, Microsoft Azure and Google Cloud; provide the database company with a competitive advantage in AI given the hyperscalers’ out-sized role in that space.

MongoDB is launching a new initiative with Google Cloud to help developers leverage generative AI and build AI-powered applications. Expanding on the existing MongoDB-Google Cloud partnership, developers can use MongoDB Atlas and partner integrations with Google Cloud’s Vertex AI large language models, along with new quick-start architecture reviews with MongoDB and Google Cloud professional services, to jump-start software development.

At the New York event MongoDB also debuted the MongoDB AI Innovators Program, which provides organizations developing AI technology with access to credits for working with MongoDB Atlas, partnership opportunities within the MongoDB partner ecosystem, and joint go-to-market activities. The program includes the AI Startups track for early-stage companies and the AI Amplify for more established companies.

Topping the development announcements at the New York event is a slew of new capabilities for MongoDB Atlas that the company is now offering on a preview basis.

MongoDB Atlas Vector Search, now in public preview, is built into the core platform, enabling organizations to build next-generation applications that use generative AI for information retrieval and personalization to enhance end-user experiences and improve productivity, according to the company. MongoDB Atlas Search Nodes, currently in private preview, provides dedicated resources for scaling search workloads independent of their database, enabling workload isolation, resource optimization and better performance at scale.

The new MongoDB Atlas Stream Processing helps developers build applications that can better analyze high-velocity streams of complex data in real-time and adjust application behavior in response.

“The real world is not static. Every business is driven by software, people are basically building real-time businesses. Software also has to be real time. Software applications need to become more real time as ever,” CEO Ittycheria said in his keynote while introducing MongoDB Atlas Stream Processing.

Enhancements to the database’s MongoDB Time Series collections functionality offer improved scalability and the ability to modify time series data after data ingestion. And new multi-cloud options add Microsoft Azure support to MongoDB Atlas Online Archive and Atlas Data Federation, in addition to Amazon Web Services.

MongoDB also announced the general availability of MongoDB Relational Migrator, a tool for simplifying the transformation of aging applications running on legacy relational database systems and migrating them to the MongoDB Atlas database and its document-based data models.

Relational Migrator will support both one-time migration and continuous change data capture use cases. It analyzes legacy databases, automatically generates new data schema and code, and executes a migration to MongoDB Atlas, according to the company.

“I feel this is game-changing for systems integrators, ISVs, and the cloud providers themselves, Chhabra said.

“We think this will help customers modernize to MongoDB faster, more affordably, which will definitely help the SIs because they sell consulting, they’re looking for a competitive angle to do that, to win deals, and this tooling helps them do that,” the channel chief said. “We think it’ll help the cloud partners because they want to drive more applications to the cloud, driving consumption, we will help them do that. And it will help ISVs because many ISVs are trying to transform from on-premises to SaaS and they need a way to move from a legacy architecture to MongoDB.”

Partners already working with Relational Migrator include systems integrators Accenture and Capgemini and digital consultancy Globant.

“Along with Accenture’s own capabilities and solutions, the release of MongoDB Relational Migrator will enable customers to accelerate their modernization strategies,” said Stephen Meyer, Accenture associate director, cloud first software engineering, NoSQL lead, in a statement. “Our partnership [with MongoDB] helps enterprises unlock value from data by modernizing and building new applications faster.”

“We are seeing more and more customers leverage MongoDB’s Relational Migrator to migrate from traditional relational databases to MongoDB Atlas with no downtime, making it a seamless and efficient solution,” said Nicolas Avila, Globant chief technology officer for North America, in a statement.

MongoDB is also launching MongoDB Atlas for Industries, an initiative to provide developers with industry-specific expertise, programs, partnerships and integrated solutions to accelerate cloud adoption and application modernization. The effort includes workshops with industry experts from MongoDB and partners, access to the company’s industry-specific partner integrations and toolchains, and “industry knowledge accelerators” – tailored MongoDB University courses and learning materials.

The first set of vertical-industry solutions in MongoDB Atlas for Industries covers the rapidly changing financial services industry with offerings for manufacturing and automotive, insurance, healthcare, retail and other industries to follow over the next year.

Rick Whiting

Rick Whiting has been with CRN since 2006 and is currently a feature/special projects editor. Whiting manages a number of CRN’s signature annual editorial projects including Channel Chiefs, Partner Program Guide, Big Data 100, Emerging Vendors, Tech Innovators and Products of the Year. He also covers the Big Data beat for CRN. He can be reached at rwhiting@thechannelcompany.com.

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MongoDB, Inc. MDB shares are trading higher Thursday after the company announced several new product launches.

What To Know: The MongoDB AI Innovators Program provides organizations building AI technology access to credits for MongoDB Atlas, partnership opportunities in the MongoDB Partner Ecosystem, and go-to-market activities with MongoDB to accelerate innovation and time to market.

The MongoDB Atlas for Industries helps organizations accelerate cloud adoption and modernization by leveraging industry-specific expertise, programs, partnerships, and integrated solutions.

Five new products and features were announced for the company’s industry-leading developer data platform, MongoDB Atlas, that make it significantly faster and easier for customers to build modern applications, for any workload or use case.

General availability of MongoDB Relational Migrator, a new tool that simplifies application migration and transformation, was announced.

A new initiative in partnership was announced with Google Cloud to help developers accelerate the use of generative AI and build new classes of applications.

Also, new capabilities for the world’s most popular NoSQL database for building modern applications faster and with less heavy lifting were announced as well.

“Our long-term vision is to create a developer data platform that removes as much builder friction as possible and makes it easier for developers to do what they do best—build,” said Andrew Davidson, Senior Vice President of Product at MongoDB. “Developers choose MongoDB Atlas because it’s the best place to quickly build applications that can make the most out of their data.”

“We continually hear from developers that they want to be able to use even more tools seamlessly on MongoDB Atlas, so with these additional integrations and expanded features, we are taking another step in fulfilling our mission to meet developers where they are and to provide the best possible building experience with the least amount of friction.”

Related Link: What’s Going On With Palo Alto Networks?

MDB Price Action: Shares of MDB were up 3.60% at $386.38 at the time of publication, according to Benzinga Pro.

Image by RAEng_Publications from Pixabay

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1 Magnificent Growth Stock That Could Shoot 2,112% Higher by 2026, According to Wall Street

4 Top Dividend Payers of the S&P 500

2 Super Stocks That Could Turn $200,000 Into $1 Million by 2033

Want the Max $4,555 Social Security Benefit? Here’s the Salary You Need

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Fulton Bank N.A., a financial institution located in Pennsylvania, recently bought $256,000 worth of stock in MongoDB, Inc. (NASDAQ:MDB), according to a disclosure report filed with the Securities and Exchange Commission (SEC). The bank purchased 1,097 shares of the data platform company during Q1 of this year. While this may seem like a small investment for Fulton Bank N.A., it exemplifies an important market shift towards tech companies offering data platforms.

The MongoDB platform is a versatile database system designed to be used by businesses worldwide. The cloud-based solution is offered as both a commercial and free-to-download version of its software. Currently, many technology platforms are using technologies such as blockchain or artificial intelligence that require large amounts of data storage and retrieval capabilities. This is where MongoDB comes into play – offering powerful and flexible solutions which make it possible for these sophisticated systems to function at optimal levels.

Analysts also seem bullish on the future prospects for MDB shares, with Stifel Nicolaus lifting their price target from $240 to $375 dollars on June 2nd while The Goldman Sachs Group raised their target price from $280 to $420 dollars. Onboarding more than 20 analysts on its coverage slate shows how popular MDB has become among investors looking for exposure to the growing market demand.

While one solitary analyst rated the stock as a sell rating, there is no doubt that MDB has seduced many banks and investment companies who now offer this hot property. Shares in MongoDB have risen steadily over recent years due to heightened competition from other database firms forcing well-respected brokers like Needham & Company LLC lift their target price from $250 up to the huge figure of $430!

Based on data analyzed by Bloomberg, MongoDB currently holds a “Moderate Buy” consensus rating from economic experts with an average price target hovering around $328 per share; this represents continued strength and growth in what is quickly becoming known as the hottest sector. The recent investment by Fulton Bank N.A. underscores the growing importance of data platforms and highlights what may be divergent opinion from those who are strictly devoted to physical assets, but the final numbers spell a resounding “Yes” according to those that preach following tech companies’ lead when it comes to money questions, especially in these unprecedented times dominated by software operations all around us.

Investment and Shareholder Moves at MongoDB Inc: A Global Provider of General-Purpose Database Solutions

MongoDB Inc. is a global provider of a general-purpose database platform that offers its clients varied and efficient solutions for their data management needs. With offices worldwide, MongoDB offers their services under numerous packages such as the MongoDB Atlas – a multi-cloud hosting database-as-a-service package; MongoDB Enterprise Advanced – a commercial database server; and Community Server – which is a free-to-download version of their database aimed at developers.

Hedge funds are seeking to enhance their stakes in the company led by Cherry Creek Investment Advisors with an increment of 1.5% during the last quarter for 3283 shares now valued at $646,000. Additionally, Allworth Financial LP raised its stake by 12.9% after acquiring an additional 58 shares now worth approximately $100,000 in total during the fourth quarter of last year while Cetera Advisor Networks LLC increased its stake in MDB by 7.4%. The First Republic Investment Management also raised its stake by 1.0%, making consecutive raises this year.

Further adding to shareholder value, insiders have been selling shares since April this year. Director Hope F Cochran sold off over 2000 shares of $MDB stock totaling to $811,315 on June 15th marking her second sell this year alone while CRO Cedric Pech sold off about 720 shares earlier in April valued at over $164,397.

As per CNBC’s analysis report obtained from NASDAQ, MDB opened today (July ninth) with the target fixed at $372.96 based on current market analyses having moved above most other trends including those based on the financial performance reports filed earlier last month on June first where they reported Q1 EPS of $.56 and net profit margin remaining negative.

In conclusion, investors seeking diversified solutions through trusted databases can always rely on MongoDB’s deep industry experience backed up by state-of-the-art technology aimed towards providing its clients with reliable data storage, security, and efficient processing.

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After trying to broaden its user base to include traditional database professionals last year, MongoDB is switching gears, adding features to turn its NoSQL Atlas database-as-a-service (DBaaS) into a more complete data platform for developers, including capabilities that support building generative AI applications.

In addition to introducing vector search for Atlas and integrating Google Cloud’s Vertex AI foundation models, the company announced a variety of new capabilities for the DBaaS at its MongoDB.local conference in New York Thursday, including new Atlas Search, data streaming, and querying capabilities.

“Everything that MongoDB has announced can be seen as a move to make Atlas a more comprehensive and complete data platform for developers,” said Doug Henschen, principal analyst at Constellation Research. “The more that MongoDB can provide to enable developers with all the tools that they need, the stickier the platform becomes for those developers and the enterprises they work for.”

Henschen’s perspective seem reasonable, given that the company has been competing with cloud data platform suppliers such as Snowflake, which offers a Native Application Framework, and Databricks, which recently launched Lakehouse Apps.  

Vector search helps build generative AI apps

In an effort to help enterprise build applications based on generative AI from data stored in MongoDB, the company has introduced a vector search capability inside Atlas, dubbed Atlas Vector Search.

This new search capability, according to the company, will help support a new range of workloads, including semantic search with text, image search, and highly personalized product recommendations.

The search runs on vectors — multidimensional mathematical representations of features or attributes of raw data that could include text, images, audio or video, said Matt Aslett, research director at Ventana Research.

“Vector search utilizes vectors to perform similarity searches by enabling rapid identification and retrieval of similar or related data,” Aslett said, adding that vector search can also be used to complement large language models (LLMs) to reduce concerns about accuracy and trust through the incorporation of approved enterprise content and data.

MongoDB Atlas’ Vector Search will also allow enterprises to augment the capabilities of pretrained models such as GPT-4 with their own data via the use of open source frameworks such as LangChain and LlamaIndex, the company said.

These frameworks can be used to access LLMs from MongoDB partners and model providers, such as AWS, Databricks, Google Cloud, Microsoft Azure, MindsDB, Anthropic, Hugging Face and OpenAI, to generate vector embeddings and build AI-powered applications on Atlas, it added.

MongoDB partners with Google Cloud

MongoDB’s partnership with Google Cloud to integrate Vertex AI capabilities is meant to accelerate the development of generative AI-based applications.  Vertex AI, according to the company, will provide the text embedding API required to generate embeddings from enterprise data stored in MongoDB Atlas.

These embeddings can be later combined with the PaLM text models to create advanced functionality like semantic search, classification, outlier detection, AI-powered chatbots, and text summarization.

The partnership will also allow enterprises to get hands-on assistance from MongoDB and Google Cloud service teams on data schema and indexing design, query structuring, and fine-tuning AI models.

Databases from Dremio, DataStax and Kinetica are also adding generative AI capabilities.

MongoDB’s move to add vector search to Atlas is not unique but it will enhance the company’s competitiveness, Aslett said. “There is a growing list of specialist vector database providers, while multiple vendors of existing databases are working to add support to bring vector search to data already stored in their data platforms,” Aslett said.

Managing real-time streaming data in a single interface

In order to help enterprises manage real-time streaming data from multiple sources in a single interface, MongoDB has added a stream processing interface to Atlas.

Dubbed Atlas Stream Processing, the new interface, which can process any kind of data and has a flexible data model, will allow enterprises to analyze data in real-time and adjust application behavior to suit end customer needs, the company said.

Atlas Stream Processing bypasses the need for developers to use multiple specialized programming languages, libraries, application programming interfaces (APIs), and drivers, while avoiding the complexity of using these multiple tools, MongoDB claimed.

The new interface, according to Aslett, helps developers to work with both streaming and historical data using the document model.

“Processing data as it is ingested enables data to be queried continuously as new data is added, providing a constantly updated, real-time view that is triggered by the ingestion of new data,” Aslett said.

A report from Ventana Research claims that more than seven in 10 enterprises’ standard information architectures will include streaming data and event processing by 2025, so that they can provide better customer experiences.

Atlas Stream Processing, according to SanjMo’s principal analyst Sanjeev Mohan, can also be used by developers to perform functions like aggregations, as well as filter and do anomaly detection on data that is in Kafka topics, Amazon Kinesis or even MongoDB change data capture.

The flexible data model inside Atlas Stream Processing can also be modified over time to suit needs, the company said.

The addition of the new interface to Atlas can be seen as a move to play catchup with rival data cloud providers such as Snowflake and Databricks, which have already introduced features for processing real-time data, noted Constellation’s Henschen.

New Atlas search features

In order to help enterprises to maintain database and search performance on Atlas, the company has introduced a new feature, dubbed Atlas Search Nodes, that isolates search workloads from database workloads.

Targeted at enterprises that have already scaled their search workloads on MongoDB, Atlas Search Nodes provides dedicated resources and optimizes resource utilization to support performance of these specific workloads, including vector search, the company said.

“Enterprises may find that dedicating nodes in a cluster, specifically to search, can support operational efficiency by avoiding performance degradation on other workloads,” Aslett said, adding that this is a capability that was being adopted by multiple providers of distributed databases.  

MongoDB’s updates to Atlas also include a new time-series data editing feature that the company claims is usually not allowed in most time-series databases.

The company’s Time Series Collections features will now allow enterprises to modify time-series data resulting in better storage efficiency, accurate results, and better query performance, the company said.  

The feature to modify time-series data will help most enterprises, according to Mohan.

Other updates to MongoDB Atlas include the ability to tier and query databases on Microsoft Azure using the Atlas Online Archive and Atlas Data Federation features, the company said, adding that Atlas already supported tiering and querying on AWS.

MongoDB Atlas for financial services and other industries

As part of the updates announced at its MongoDB.local conference, the company said that it will be launching a new industry-specific Atlas database program for financial services, followed by other industry sectors such as retail, healthcare, insurance, manufacturing and automotive.

These industry-specific programs will see the company offer expert-led architectural design reviews, technology partnerships via workshops and other instruments for enterprises to build vertical-specific solutions. The company will also offer tailored MongoDB University courses and learning materials to enable developers for their enterprise projects.

While the company did not immediately provide information on the availability and pricing of the new features, it said that it was making its Relational Migrator tool generally available.

The tool is designed to help enterprises move their legacy databases to modern document-based databases.

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More about the company

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MongoDB Atlas expands programming language support to simplify deploying resources on AWS using infrastructure-as-code

New Kotlin Driver for MongoDB enables developers to build server-side applications on MongoDB with the Kotlin programming language

MongoDB Atlas Kubernetes Operator now simplifies working with containerized applications with the option to import deployments using a single command

MongoDB-supported PyMongoArrow library allows data scientists and machine learning practitioners to work with data stored in MongoDB to build modern applications with less heavy lifting

NEW YORK, June 22, 2023 /PRNewswire/ — MongoDB, Inc. (NASDAQ: MDB) today at its developer conference MongoDB.local NYC announced new capabilities for the world’s most popular NoSQL database for building modern applications faster and with less heavy lifting. The new tools announced today empower developers to do their best work—including additional programming language support for using infrastructure-as-code (IaC) to deploy MongoDB Atlas on AWS and building server-side applications with Kotlin, streamlined capabilities for MongoDB Atlas Kubernetes Operator, and the general availability of the the PyMongoArrow library for more efficient data analysis using Python. Together, these new capabilities expand MongoDB’s mission to meet developers where they are by integrating the tools they love in a single developer data platform to make it faster and easier to build applications. To learn more about building with MongoDB, visit mongodb.com.

Tens of thousands of customers and millions of developers rely on MongoDB Atlas every day as their preferred developer data platform to power applications because of its flexible data model, speed to deploy new features, and performance at scale. Developers also love using MongoDB Atlas because it eliminates the undifferentiated heavy lifting of infrastructure management and enables going from idea to innovation quickly with a unified developer data platform. However, for certain use cases, developers want to use specialized tools with MongoDB Atlas to better integrate their established workflows and have more granular control over the operational experience. For example, developers who prefer provisioning MongoDB Atlas clusters with IaC on AWS or building server-side applications want to use their programming language of choice. Further, many developers want to use the MongoDB Atlas command line interface (CLI) for more tasks in their specific workflows, while other developers want to be able to use additional programming languages for data science, machine learning, and application-driven analytics.

The new features and integrations announced today reinforce MongoDB’s commitment to providing the best developer experience for building and iterating on ideas rather than wrangling tooling:

• Additional options for deploying MongoDB Atlas on AWS: Developers can now use additional programming languages to create, manage, and update MongoDB Atlas resources using IaC with the AWS Cloud Development Kit (CDK). MongoDB provides support for IaC on AWS with the AWS CloudFormation Public Registry, AWS Partner Solution Deployments, and the AWS CDK. However, many developers want to use additional programming languages beyond Javascript and Typescript. Now, developers can use IaC with the AWS CDK to manage MongoDB Atlas resources with C#, Go, Java, and Python—making it easier for developers to streamline workflows using a wider variety of programming languages and reduce the amount of time they spend managing infrastructure. To get started, visit mongodb.com/atlas/aws-cloudformation
• Expanded programming language support for server-side Kotlin: The Kotlin Driver for MongoDB now allows developers to build highly performant server-side applications on MongoDB using Kotlin. Previously, developers could use the MongoDB Realm Kotlin SDK for client-side development, but server-side developers relied on a community-created driver without official MongoDB support or had to write extensive custom code. As a result, developers faced longer software development cycles to build server-side Kotlin applications on MongoDB and risked application reliability without a fully supported MongoDB Kotlin driver. Now, with the Kotlin Driver for MongoDB, developers can use a best-in-class Kotlin experience for server-side application development to get from idea to production more quickly and reliably. To get started, visit mongodb.com/docs/drivers/kotlin/coroutine/current/.
• Streamlined MongoDB Atlas Kubernetes Operator functionality: Developers use the MongoDB Atlas Kubernetes Operator to manage projects and database clusters, reduce the effort required to automate configuration and management of MongoDB Atlas, and take advantage of containerized application development. However, developers want a simpler way to install and set up the MongoDB Atlas Kubernetes Operator to reduce friction and manage applications more quickly. Using the MongoDB Atlas CLI, developers can now install the MongoDB Atlas Kubernetes Operator and generate security credentials for quick and easy setup to reduce operational overhead. Developers then have the option to import existing MongoDB Atlas projects and deployments with a single command. This new enhancement dramatically simplifies how developers use Kubernetes with MongoDB Atlas and streamlines their workflows by providing greater speed when working with containers. To get started, visit mongodb.com/kubernetes/atlas-operator.
• Easier data processing and analytics on MongoDB using Python: With the general availability of the open source PyMongoArrow library maintained by MongoDB, developers and data analysts can use a Python-based analytics stack to extract insights from data on MongoDB and build data-driven applications more quickly. Building modern, intelligent applications that take advantage of application-driven analytics requires harnessing insights from application data and incorporating those insights back into applications to adjust business logic in real time. The PyMongoArrow library allows developers to efficiently convert data stored on MongoDB using popular frameworks (e.g., Apache Arrow Tables, Pandas DataFrames, or Numpy Arrays) and will receive ongoing development and support from MongoDB as the needs of Python-based analytics stacks evolve. With PyMongoArrow, developers, data scientists, and machine learning practitioners have the tools they need to more efficiently manipulate and analyze data on MongoDB with Python to reduce software-development friction. To get started, visit mongo-arrow.readthedocs.io/en/latest.

“Our long-term vision is to create a developer data platform that removes as much builder friction as possible and makes it easier for developers to do what they do best—build,” said Andrew Davidson, Senior Vice President of Product at MongoDB. “Developers choose MongoDB Atlas because it’s the best place to quickly build applications that can make the most out of their data. We continually hear from developers that they want to be able to use even more tools seamlessly on MongoDB Atlas, so with these additional integrations and expanded features, we are taking another step in fulfilling our mission to meet developers where they are and to provide the best possible building experience with the least amount of friction.”

RedMonk is an industry analyst firm that exists to help companies understand and work with developers. “While the explosion in database, development, and infrastructure tooling in recent years has put more and more resources into the hands of developers, it’s also led to a heavily fragmented and inefficient developer experience,” said Stephen O’Grady, Principal Analyst at RedMonk. “Increasingly, however, enterprises are focusing on opportunities to thoughtfully retool their workflows to make them faster and more integrated. The C-suite is making these investments not just because it benefits developers by delivering a higher quality and lower friction experience, but because having more efficient developers that are able to iterate more quickly is the single best mechanism for improving an organization’s overall velocity.”

MongoDB Developer Data Platform
MongoDB Atlas is the leading multi-cloud developer data platform that accelerates and simplifies building with data. MongoDB Atlas provides an integrated set of data and application services in a unified environment to enable developer teams to quickly build with the capabilities, performance, and scale modern applications require.

About MongoDB
Headquartered in New York, MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, our developer data platform is a database with an integrated set of related services that allow development teams to address the growing requirements for today’s wide variety of modern applications, all in a unified and consistent user experience. MongoDB has tens of thousands of customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses. To learn more, visit mongodb.com.

Forward-Looking Statements

This press release includes certain “forward-looking statements” within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including statements concerning MongoDB’s new capabilities for MongoDB Atlas to build new classes of applications. These forward-looking statements include, but are not limited to, plans, objectives, expectations and intentions and other statements contained in this press release that are not historical facts and statements identified by words such as “anticipate,” “believe,” “continue,” “could,” “estimate,” “expect,” “intend,” “may,” “plan,” “project,” “will,” “would” or the negative or plural of these words or similar expressions or variations. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including, without limitation: the impact the COVID-19 pandemic may have on our business and on our customers and our potential customers; the effects of the ongoing military conflict between Russia and Ukraine on our business and future operating results; economic downturns and/or the effects of rising interest rates, inflation and volatility in the global economy and financial markets on our business and future operating results; our potential failure to meet publicly announced guidance or other expectations about our business and future operating results; our limited operating history; our history of losses; failure of our platform to satisfy customer demands; the effects of increased competition; our investments in new products and our ability to introduce new features, services or enhancements; our ability to effectively expand our sales and marketing organization; our ability to continue to build and maintain credibility with the developer community; our ability to add new customers or increase sales to our existing customers; our ability to maintain, protect, enforce and enhance our intellectual property; the growth and expansion of the market for database products and our ability to penetrate that market; our ability to integrate acquired businesses and technologies successfully or achieve the expected benefits of such acquisitions; our ability to maintain the security of our software and adequately address privacy concerns; our ability to manage our growth effectively and successfully recruit and retain additional highly-qualified personnel; and the price volatility of our common stock. These and other risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission (“SEC”), including under the caption “Risk Factors” in our Quarterly Report on Form 10-Q for the quarter ended April 30, 2023, filed with the SEC on June 2, 2023 and other filings and reports that we may file from time to time with the SEC. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

Media Relations
MongoDB
[email protected]

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SOURCE MongoDB, Inc.

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Project lead: Let’s build some data-centric apps!

Developers: Hmm, you sound too keen – and anyway, how screwy is the requirements-gathering process and what crazy requests have we got from the user base?

Project lead: Relax, the requirements only evidence 10% of the normal insanity and we’re building in a data-developer platform environment specifically designed to reduce operational overhead in the face of deployment across cloud services making full use of Infrastructure-as-Code (IaC) and leveraging code libraries that allows data scientists and Machine Learning (ML) practitioners to work with data stored to build modern applications with less heavy lifting.

Developers: Have you been drinking?

Back in the real world, some of the above may actually form part of the new fabric of conversations in cloud-native data-driven software application development project environments. MongoDB certainly hopes so, the company used its developer conference MongoDB.local NYC to announce new capabilities for its NoSQL database.

The new tools include additional programming language support for using Infrastructure-as-code (IaC) to deploy MongoDB Atlas on AWS and building server-side applications with Kotlin, streamlined capabilities for MongoDB Atlas Kubernetes Operator and the general availability of the PyMongoArrow library for more efficient data analysis using Python. 

NOTE: Kotlin is a cross-platform, statically typed, general-purpose high-level programming language with type inference designed to make coding concise, cross-platform (and fun) and is said to be Google’s preferred language for Android app development.

Taken as a whole, MongoDB says its new capabilities expand the company’s mission to meet developers where they are by integrating the tools they love in a single developer data platform.

Article originally posted on mongodb google news. Visit mongodb google news