Posted on mongodb google news. Visit mongodb google news

p” class=”inline-offer pre-churn-offer”>

Redeem now

• AI may be impressive, but it’s not revolutionary yet, MongoDB’s CEO said.
• Dev Ittycheria said we need to see more integration of AI with practical applications.
• AI-powered solutions need to incorporate real-time data into their responses to be the most useful, he added.

Advertisement

At least one executive thinks AI still has a ways to go for it to truly change the way we work and communicate in a big way.

“My life has not been transformed by AI,” MongoDB CEO Dev Ittycheria said in an interview with TechCrunch. “Yes, maybe I can write an email better through all those assistants, but it’s not fundamentally transformed my life. Whereas the internet has completely transformed my life.”

That’s not to say that Ittycheria is dismissing the potential of AI to eventually revolutionize the workplace, but the value of any new technology accrues “at the bottom layer first,” he told the tech publication.

Related stories

Ittycheria said that the “real value” of AI will come once existing platforms like OpenAI’s ChatGPT are fully integrated into more practical, everyday applications. Helping people develop applications — and those built on top of AI models — is MongoDB’s “business,” he added. The database software firm has its own AI-powered projects in the mix, including its Atlas suite of data services.

Advertisement

AI services will have to incorporate “real-time data” to make them transformative to the average person, Ittycheria said.

“Maybe something’s happening in the stock market, maybe it’s time to buy or sell, or it’s time to hedge,” he told TechCrunch. “I think that’s where we will start seeing much more sophisticated apps, where you can embed real-time data along with all the reasoning.”

The AI boom has thrown the tech world into a frenzy, as companies large and small explore new ways of leveraging it. New tools are already starting to change areas like management culture.

Bill Gates has compared AI to seismic tech advancements like the invention of the PC or the internet.

Advertisement

But Ittycheria isn’t the only one suggesting the transformative impacts of AI are still to come. Mark Zuckerberg, who has doubled down on Meta’s AI efforts, recently warned wary investors that their efforts may take “several years” to bear fruit.

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

Posted on mongodb google news. Visit mongodb google news

The strength reported by Microsoft (MSFT) and Google (GOOG) (GOOGL) in their respective cloud computing units last week could have positive implications for the broader cloud computing software industry as a whole, investment firm Baird said.

“Strong data points to kick off earnings season from both Azure and Google Cloud, which should be directionally positive for our cloud data leaders – SNOW, MDB, DDOG and DT – boosting those stocks to end the week,” analysts at the investment firm said, referencing Snowflake (NYSE:SNOW), MongoDB (NASDAQ:MDB), Datadog (NASDAQ:DDOG) and Dynatrace (NYSE:DT).

Snowflake was up 0.8% in mid-day trading, while MongoDB, Datadog and Dynatrace fell at least 1% each.

A consensus of analysts expects Seattle-based Amazon to earn $0.83 on revenue of $142.56B in sales when it reports on April 30, implying a rise of 11.9% during the quarter.

Investors will also look into capital expense for the quarter, especially after the company said it anticipates spending for 2024 to increase year-over-year, primarily driven by increased infrastructure to support AWS growth and additional investments in generative AI among others.

MongoDB is slated to host an investor event on May 2, followed by Datadog, which will discuss its first-quarter results on May 7. Snowflake is set to discuss its first-quarter results of fiscal 2025 on May 22.

Dynatrace has not yet set a date, according to its investor relations website.

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

Posted on mongodb google news. Visit mongodb google news

On Monday, MongoDB (MDB) received an upgrade to its Relative Strength (RS) Rating, from 65 to 75.

X



This proprietary rating measures technical performance by showing how a stock’s price action over the last 52 weeks measures up against that of the other stocks in our database.

Decades of market research reveals that the market’s biggest winners often have an 80 or better RS Rating as they begin their largest runs. See if MongoDB can continue to show renewed price strength and clear that threshold.

How To Invest In Stocks In Both Bull And Bear Markets

While now is not an ideal time to invest, see if the stock is able to form a chart pattern and break out.

MongoDB showed 51% EPS growth last quarter. Revenue rose 27%.

MongoDB earns the No. 4 rank among its peers in the Computer Software-Database industry group. Elastic (ESTC) is the top-ranked stock within the group.

RELATED:

IBD Stock Rating Upgrades: Rising Relative Strength

Why Should You Use IBD’s Relative Strength Rating?

How Relative Strength Line Can Help You Judge A Stock

Ready To Grow Your Investing Skills? Join An IBD Meetup Group!

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

Posted on mongodb google news. Visit mongodb google news

Key Insights

• The projected fair value for MongoDB is US$386 based on 2 Stage Free Cash Flow to Equity
• With US$384 share price, MongoDB appears to be trading close to its estimated fair value
• Analyst price target for MDB is US$447, which is 16% above our fair value estimate

How far off is MongoDB, Inc. (NASDAQ:MDB) from its intrinsic value? Using the most recent financial data, we’ll take a look at whether the stock is fairly priced by projecting its future cash flows and then discounting them to today’s value. One way to achieve this is by employing the Discounted Cash Flow (DCF) model. Believe it or not, it’s not too difficult to follow, as you’ll see from our example!

We generally believe that a company’s value is the present value of all of the cash it will generate in the future. However, a DCF is just one valuation metric among many, and it is not without flaws. If you still have some burning questions about this type of valuation, take a look at the Simply Wall St analysis model.

View our latest analysis for MongoDB

Crunching The Numbers

We’re using the 2-stage growth model, which simply means we take in account two stages of company’s growth. In the initial period the company may have a higher growth rate and the second stage is usually assumed to have a stable growth rate. To begin with, we have to get estimates of the next ten years of cash flows. Where possible we use analyst estimates, but when these aren’t available we extrapolate the previous free cash flow (FCF) from the last estimate or reported value. We assume companies with shrinking free cash flow will slow their rate of shrinkage, and that companies with growing free cash flow will see their growth rate slow, over this period. We do this to reflect that growth tends to slow more in the early years than it does in later years.

Generally we assume that a dollar today is more valuable than a dollar in the future, so we discount the value of these future cash flows to their estimated value in today’s dollars:

10-year free cash flow (FCF) estimate

(“Est” = FCF growth rate estimated by Simply Wall St)
Present Value of 10-year Cash Flow (PVCF) = US$6.0b

We now need to calculate the Terminal Value, which accounts for all the future cash flows after this ten year period. For a number of reasons a very conservative growth rate is used that cannot exceed that of a country’s GDP growth. In this case we have used the 5-year average of the 10-year government bond yield (2.3%) to estimate future growth. In the same way as with the 10-year ‘growth’ period, we discount future cash flows to today’s value, using a cost of equity of 7.3%.

Terminal Value (TV)= FCF₂₀₃₃ × (1 + g) ÷ (r – g) = US$2.2b× (1 + 2.3%) ÷ (7.3%– 2.3%) = US$45b

Present Value of Terminal Value (PVTV)= TV / (1 + r)¹⁰= US$45b÷ ( 1 + 7.3%)¹⁰= US$22b

The total value, or equity value, is then the sum of the present value of the future cash flows, which in this case is US$28b. In the final step we divide the equity value by the number of shares outstanding. Compared to the current share price of US$384, the company appears about fair value at a 0.5% discount to where the stock price trades currently. Remember though, that this is just an approximate valuation, and like any complex formula – garbage in, garbage out.

Important Assumptions

Now the most important inputs to a discounted cash flow are the discount rate, and of course, the actual cash flows. You don’t have to agree with these inputs, I recommend redoing the calculations yourself and playing with them. The DCF also does not consider the possible cyclicality of an industry, or a company’s future capital requirements, so it does not give a full picture of a company’s potential performance. Given that we are looking at MongoDB as potential shareholders, the cost of equity is used as the discount rate, rather than the cost of capital (or weighted average cost of capital, WACC) which accounts for debt. In this calculation we’ve used 7.3%, which is based on a levered beta of 1.092. Beta is a measure of a stock’s volatility, compared to the market as a whole. We get our beta from the industry average beta of globally comparable companies, with an imposed limit between 0.8 and 2.0, which is a reasonable range for a stable business.

SWOT Analysis for MongoDB

Next Steps:

Valuation is only one side of the coin in terms of building your investment thesis, and it ideally won’t be the sole piece of analysis you scrutinize for a company. DCF models are not the be-all and end-all of investment valuation. Preferably you’d apply different cases and assumptions and see how they would impact the company’s valuation. If a company grows at a different rate, or if its cost of equity or risk free rate changes sharply, the output can look very different. For MongoDB, we’ve compiled three important elements you should consider:

1. Risks: Consider for instance, the ever-present spectre of investment risk. We’ve identified 2 warning signs with MongoDB , and understanding these should be part of your investment process.
2. Future Earnings: How does MDB’s growth rate compare to its peers and the wider market? Dig deeper into the analyst consensus number for the upcoming years by interacting with our free analyst growth expectation chart.
3. Other High Quality Alternatives: Do you like a good all-rounder? Explore our interactive list of high quality stocks to get an idea of what else is out there you may be missing!

PS. The Simply Wall St app conducts a discounted cash flow valuation for every stock on the NASDAQGM every day. If you want to find the calculation for other stocks just search here.

Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.

This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.

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

Article originally posted on InfoQ. Visit InfoQ

This week’s Java roundup for April 22nd, 2024 features news highlighting: the release of WildFly 32; JEP 476, Module Import Declarations (Preview), JEP 474, ZGC: Generational Mode by Default, and JEP 467, Markdown Documentation Comments, proposed to target for JDK 23; Hibernate ORM 6.5; and JobRunr 7.1.

OpenJDK

One week after having been declared a candidate, JEP 476, Module Import Declarations (Preview), has been promoted from Candidate to Proposed to Target for JDK 23. This preview feature proposes to enhance the Java programming language with the ability to succinctly import all of the packages exported by a module with a goal to simplify the reuse of modular libraries without requiring to import code to be in a module itself. The review is expected to conclude on May 1, 2024.

JEP 474, ZGC: Generational Mode by Default, has also been promoted from Candidate to Proposed to Target for JDK 23. This JEP proposes to use the Z Garbage Collector (ZGC) from non-generational to generational mode by default. The non-generational mode will be deprecated and removed in a future JDK release. This will ultimately reduce the cost of maintaining the two modes such that future development can primarily focus on JEP 439, Generational ZGC. The review is expected to conclude on April 30, 2024. InfoQ will follow up with a more detailed news story.

JEP 467, Markdown Documentation Comments, has been promoted from Candidate to Proposed to Target for JDK 23. This feature proposes to enable JavaDoc documentation comments to be written in Markdown rather than a mix of HTML and JavaDoc @ tags. This will allow for documentation comments that are easier to write and easier to read in source form. The review is expected to conclude on May 4, 2024. InfoQ will follow up with a more detailed news story.

JDK 23

Build 20 of the JDK 23 early-access builds was made available this past week featuring updates from Build 19 that include fixes for various issues. Further details on this release may be found in the release notes.

BellSoft

BellSoft has released versions 24.0.1 for JDK 22, 23.1.3 for JDK 21 and 23.0.4 for JDK 17 of their Liberica Native Image Kit builds as part of the Oracle Critical Patch Update for April 2024 to address several security and bug fixes. A total of 10 CVEs have been resolved. These include: CVE-2023-41993, a vulnerability in which processing web content may lead to arbitrary code execution; and CVE-2024-21085, a vulnerability in which an unauthenticated attacker, with network access via multiple protocols, can compromise Oracle Java SE and Oracle GraalVM Enterprise Edition resulting in the unauthorized ability to cause a partial denial of service.

Spring Framework

Versions 3.3.0-M1 3.2.4 and 3.1.11 of Spring Shell have been released featuring notable resolutions to issues such as: use of the GridView class with zero column/row sizes causing an item to be placed into the bottom-right when user expects it to be in the top-left; and a race condition and resulting ConcurrentModificationException, primarily seen on WindowsOS, from the TerminalUI class when updating the screen. These releases build on Spring Boot 3.3.0-RC1, 3.2.5 and 3.1.11, respectively. More details on this release may be found in the release notes for version 3.3.0-M1, version 3.2.4 and version 3.1.11.

WildFly

The release of WildFly 32 features the version 1.0 release of WildFly Glow, a set of command-line provisioning tools that analyzes deployments and identifies the set of Galleon feature-packs and Galleon layers that are required by applications. Along with bug fixes and dependency upgrades, other new features include: support for the Jakarta MVC 2.1 specification; support for an instance of the Java SSLContext class that can dynamically delegate to different SSL contexts based on the destination’s host and port; and the ability to create channels defining component versions used to provision WildFly using the WildFly Channel project that may be separately maintained from WildFly’s feature packs. Further details on this release may be found in the release notes. InfoQ will follow up with a more detailed news story.

Micronaut

The Micronaut Foundation has released version 4.4.1 of the Micronaut Framework featuring Micronaut Core 4.4.6, bug fixes, improvements in documentation, and updates to modules: Micronaut Views, Micronaut gRPC, Micronaut Test Resources and Micronaut Maven Plugin. More details on this release may be found in the release notes.

Open Liberty

IBM has released version 24.0.0.4 of Open Liberty featuring: support for JDK 22; and updates to eight (8) Open Liberty guides to use the MicroProfile Reactive Messaging 3.0, MicroProfile 6.1 and Jakarta EE 10 specifications. There were also security fixes for: CVE-2023-51775, a vulnerability in the Javascript Object Signing and Encryption for Java (jose4j component) before version 0.9.4 that allows an attacker to cause a denial of service via a large PBES2 value; and CVE-2024-27270, a cross-site scripting vulnerability in IBM WebSphere Application Server Liberty 23.0.0.3 through 24.0.0.3 that allows an attacker to embed arbitrary JavaScript code in a specially crafted URI.

Helidon

The release of Helidon 4.0.8 ships with notable changes such as: support for a span event listener with a new SpanListener interface for improved tracing callbacks; and the use of delegation instead of inheritance from the Java BufferedOutputStream class to ensure the use of virtual thread-friendly locks in the JDK code and avoids thread pinning due to synchronized blocks in the JDK. Further details on this release may be found in the changelog.

Hibernate

The release of Hibernate ORM 6.5.0.Final delivers new features such as: Java time objects marshaled directly through the JDBC driver as defined by JDBC 4.2 to replace the use of java.sql.Date, java.sql.Time or java.sql.Timestamp classes; a configurable query cache layout to minimize higher memory consumption from storing the full data in the cache; and support for Java records as a parameter in the Jakarta Persistence @IdClass annotation; and support for auto-enabled filters. This release also includes a technical preview of the Jakarta Data specification that will be included in the upcoming release of Jakarta EE 11.

Apache Software Foundation

The release of Apache Camel 4.4.2 provides bug fixes, dependency upgrades and improvements such as: the ability to set the error handler on the route level to complement the existing error handler on the global lever in the Camel YAML DSL component; and support for the restConfiguration property in the Camel XML IO DSL component. More details on this release may be found in the release notes.

Similarly, version 4.0.5 of Apache Camel has also been released with bug fixes, dependency upgrades and improvement such as: a resolution to the PubSubApiConsumer class failing to load the POJO enum, defined in PubSubDeserializeType, on some platforms in the Camel Salesforce component; and a more robust way to obtain the correlationID for brokers in the Camel JMS component. Further details on this release may be found in the release notes.

JobRunr

Version 7.1.0 of JobRunr, a library for background processing in Java that is distributed and backed by persistent storage, has been released to deliver bug fixes, dependency upgrades and new features such as: support for virtual threads when using GraalVM Native mode; and improved initialization of the BackgroundJobServer class in Spring with improved support for JSR 310, Date and Time API. More details on this release may be found in the release notes.

Details on the new features of JobRunr 7.0.0, released on April 9, 2024 may be found in this webinar hosted by Ron Dehuysser, creator of JobRunr.

JDKUpdater

Versions 14.0.39+69 of JDKUpdater, a new utility that provides developers the ability to keep track of updates related to builds of OpenJDK and GraalVM. Introduced in mid-March by Gerrit Grunwald, principal engineer at Azul, this new release includes: a resolution to an issue related to the latest download view closing problem; and the ability to open the latest version download view from notification. Further details on this release may be found in the release notes.

TornadoVM

TornadoVM has announced that SAPMachine, a downstream distribution of OpenJDK maintained by SAP, has been added to their TornadoVM Installer utility. This complements the existing downstream distributions, namely: Oracle OpenJDK, Amazon Corretto, GraalVM and Mandrel.

Gradle

The first release candidate of Gradle 8.8 delivers: full support for JDK 22; a preview feature to configure the Gradle daemon JVM using toolchains; improved IDE performance with large projects; and improvements to build authoring, error and warning messages, the build cache, and the configuration cache. More details on this release may be found in the release notes.

Article originally posted on InfoQ. Visit InfoQ

Opening up the operating system that powers its Meta Quest devices to third-party hardware makers, Meta aims to create a larger ecosystem and make it easier for developers to create apps for larger audiences.

Dubbed Meta Horizon OS, the operating system combines mixed reality features with others focusing on social presence. The OS supports eye, face, hand, and body tracking to enable more natural interaction and social presence. It makes it possible to move people’s identities, avatars, and friend groups across virtual spaces and devices, meaning that people can be in virtual worlds that exist across mixed reality, mobile, and desktop devices.

Additionally, it supports more mixed reality-oriented features aimed to blend the digital and physical worlds such as high-resolution Passthrough, Scene Understanding, and Spatial Anchors.

Developers and creators can take advantage of all these technologies using the custom frameworks and tooling we’ve built for creating mixed reality experiences, and they can reach their communities and grow their businesses through the content discovery and monetization platforms built into the OS.

Meta sees its Horizon OS as a key enabling factor for the existence of a variety of specialized devices that better serve customers’ diverse interests in categories such as gaming, entertainment, fitness, productivity, and social presence. Examples of companies that are already building new devices based on Horizon OS include ASUS’s Republic of Games, Lenovo, and Xbox, Meta says.

At the same time, Meta is making it easier for developers to ship software on the platform, specifically by including titles featured on the App Lab in the official Meta Store. The App Lab was originally introduced to allow developers to distribute apps directly to consumers safely and securely, without requiring store approval and without sideloading.

App Lab titles will soon be featured in a dedicated section of the Store on all our devices, making them more discoverable to larger audiences. Some of the most popular apps on the Store today, like Gorilla Tag and Gym Class, began on App Lab.

On the tooling side, Meta began previewing a new spatial app framework to help developers create mixed-reality experiences.

At the hardware level, Horizon OS is tightly tied to the Snapdragon processors that power Meta Quest devices and companies building products using it are expected to use the same hardware and software stack as Meta itself.

Commenting on Meta’s announcement, John Carmack shared his view about what it could entail:

What it CAN do is enable a variety of high end “boutique” headsets, as you get with Varjo / Pimax / Bigscreen on SteamVR. Push on resolution, push on field of view, push on comfort. […] You could add crazy cooling systems and overclock everything. All with full app compatibility, but at higher price points. That would be great!

However, he maintains, “VR is held back more by software than hardware” and the effort required for Meta’s engineers to prepare the system and maintain good communication with partners is likely to slow down the further development of the system.

Other commenters chimed in, following Carmack’s take, to highlight a different scenario where Meta’s announcement could lead to the creation of a new space for VR devices, similarly to what Google achieved launching the Android platform. And almost naturally, when talk is about Meta, it’s hard not to find remarks about privacy, in this case regarding the collection of users’ gaze tracking data.

Posted on mongodb google news. Visit mongodb google news

A lot has happened since Dev Ittycheria took the reins at MongoDB, the $26 billion database company he’s led as president and CEO since September 2014. Ittycheria has taken MongoDB to the cloud, steered it through an IPO, overseen its transition from open source, launched a venture capital arm, and grown the customer base from a few hundred to something approaching 50,000.

“When I joined the company, it wasn’t clear if people would trust us to be a truly mission-critical technology,” Ittycheria told TechCrunch. “When I joined, it was doing roughly $30 million in revenue; now we’re doing close to $2 billion.”

It hasn’t all been peaches and cream, though. Five months ago, MongoDB was hit by a security breach, which, while relatively contained, did momentarily risk its reputation in an industry where reputation is paramount.

Throw into the mix the whirlwind AI revolution that has engulfed just about every industry, and there was much to discuss when TechCrunch sat down with Ittycheria at MongoDB’s new London office, which opened in Blackfriars last year.

MongoDB’s London office.  Image Credits: Paul Sawers / TechCrunch

Vector’s embrace

Databases have come a long way since IBM and Oracle first popularized relational databases more than half a century ago. The internet’s rise created demand for flexible, scalable, and cost-effective data storage and processing, paving the way for businesses such as MongoDB to thrive.

Founded in 2007 by a trio of veterans hailing from online adtech company DoubleClick (which Google acquired for $3.1 billion), MongoDB was initially called 10Gen until a rebrand to the name of its flagship product six years later. It has since emerged as one of the preeminent NoSQL databases, helping companies store and manage large volumes of data.

Prior to joining MongoDB, Ittycheria founded and exited a server automation company called BladeLogic for $900 million in 2008, and went on to serve in various board member and investor roles (including a 16-month stint at Greylock) before joining MongoDB as president and CEO coming on for 10 years ago now. Ittycheria replaced Max Schireson, who stepped down for family reasons after just 18 months in the role.

Built on a document-oriented model, MongoDB has grown off the back of the explosion in mobile and web applications where flexible, dynamic data structures are at play. The current artificial intelligence wave is driving a similar shift, with vector databases the hot new thing in town.

Like NoSQL, vector databases also specialize in unstructured data types (e.g., images, videos, social media posts), but are particularly well suited to large language models (LLMs) and generative AI. This is due to the way they store and process data in the form of vector embeddings, which convert data into numerical representations that capture relationships between different data points by storing them spatially by relevance. This makes it easier to retrieve semantically similar data and allows AI to better understand context and semantics within conversations.

While a slew of dedicated vector database startups have emerged these past few years, the incumbents have also started embracing vector, including Elastic, Redis, OpenSearch, Cassandra, and Oracle. Cloud hyperscalers, including Microsoft, Amazon, and Google have also ramped up support for vector search.

MongoDB, for its part, introduced vector search to its flagship database-as-a-service product Atlas last June, a sign that the company was preparing for the oncoming AI tsunami. This mimics other historical trends where single-function databases emerge (such as time-series) with some utility as stand-alone solutions but that might also be better integrated into a larger multi-purpose database stack. This is precisely why MongoDB introduced support for time-series databases a few years back, and why it’s doing the same with vector.

“A lot of these companies are features masking as products,” Ittycheria said of the new wave of dedicated vector products. “We built that into the platform, and that’s the value — rather using some stand-alone vector database and then your OLTP [online transaction processing] database and then your search database, we can combine all three things into one platform that makes the life of a developer and architect so much easier.”

The idea is that database providers that adopt a multipronged approach can combine all the data in one place, making life easier for developers to work with.

“There’s probably like 17 different types of databases, and probably about 300 vendors,” Ittycheria said. “There’s no customer on this planet that wants to have 17 different databases. The complexity that creates, and the cost of learning, supporting and managing those different technologies becomes overwhelming. It also inhibits innovation, because it creates this tax of complexity.”

MongoDB’s Dev Ittycheria. Image Credits: MongoDB

Too much hype

Despite the preparation, Ittycheria reckons there is too much hype around AI — for now, at least.

“My life has not been transformed by AI,” he said. “Yes, maybe I can write an email better through all those assistants, but it’s not fundamentally transformed my life. Whereas the internet has completely transformed my life.”

The theory is that despite the hullaballoo, it will take time for AI to seep into our everyday lives — and when it does, it will be through applications integrating AI, and businesses building on it.

“I think with the adoption of any new technology, we see value accrue at the bottom layer first,” Ittycheria said. “Obviously, Nvidia is making money hand over fist, and OpenAI has been the most talked about company since they launched ChatGPT. But the real value will come when people build applications on top of those technologies. And that’s the business we’re in — we’re in the business of helping people build applications.”

For now, it’s all about “simple apps,” as Ittycheria puts it. This includes chatbots for customer service, something that MongoDB itself is doing internally with CoachGTM, powered by MongoDB’s vector search, to bring its sales and customer teams instant knowledge about their products. In some ways, we’re currently in the “calculator apps” stage that the iPhone found itself in nearly 20 years ago when the concept of the App Store hit the masses.

“The real sophisticated [AI] apps will be using real-time data, being able to make real-time decisions on real-time events,” Ittycheria said. “Maybe something’s happening in the stock market, maybe it’s time to buy or sell, or it’s time to hedge. I think that’s where we will start seeing much more sophisticated apps, where you can embed real-time data along with all the reasoning.”

The SaaS path

One of the biggest developments during Ittycheria’s tenure has been the transition from a self-deployed model, where customers host MongoDB themselves and the company sells them features and services. With the launch of Atlas in 2016, MongoDB embarked on the familiar SaaS path where companies charge for removing all the complexities of self-hosting. At the time of its IPO the following year, Atlas represented 2% of MongoDB’s revenue — today that figure sits at nearly 70%.

“It’s grown very quickly, and we’ve really built that business as a public company,” Ittycheria said. “What the popularity of Atlas showed was that people are comfortable consuming infrastructure as a service. What that allows them to do is delegate what they consider ‘non-strategic functions,’ like provisioning, configuring and managing MongoDB. So they can focus on building applications that are really transforming their business.”

Another major development came when, a year after going public, MongoDB moved away from an open source AGPL license to a source-available SSPL (server side public license). In some ways, this was the bellwether of what was to come, with countless infrastructure companies going on to abandon their open source credentials to prevent the cloud giants (e.g., Amazon) from selling their own version of the service without giving back.

“We feel very happy about it [the license change],” Ittycheria said. “The reality is that while it was open source, 99.9% of the development is done by our own people — it’s not like communities contributing code. It’s not some simple, trivial application — it’s very complex code, and we need to hire senior, talented people who cost a lot of money. We didn’t think it was fair for us to spend all this money to build this product, then someone takes that free product, monetizes it, and not give us anything back. It was quite controversial in 2018, but looking back, our business has only grown faster.”

And grown it has. As with just about every tech company, MongoDB’s valuation soared during the pandemic, peaking at an all-time high of $39 billion in late 2021, before plummeting south of $10 billion within a year — roughly the same as its pre-pandemic figure.

However, MongoDB’s shares have been in ascendency in the 18 months since, hitting $35 billion just a couple of months ago, before dropping again to around $26 billion today — such is the volatile nature of the stock markets. But given the company’s relatively modest $1.8 billion valuation at the end of its first day of trading in 2017, MongoDB has performed fairly well for public market investors.

Dev Ittycheria with MongoDB colleagues at its 2017 IPO. Image Credits: MongoDB

Four months ago, though, MongoDB revealed a data breach that exposed “some customer account metadata and contact information” — it involved a phishing attack through a third-party enterprise tool (Ittycheria wouldn’t confirm which). This caused its shares to drop 3%, but in the months that followed, MongoDB’s valuation surged back to a two-year high. This highlighted how little impact the breach had on affairs at the company, certainly compared to high-profile data breaches at the likes of Equifax and Target, which hit the businesses hard and forced senior executive departures.

While MongoDB’s cybersecurity incident was significantly smaller in scope, what stood out was how quickly the whole thing went away — it was reported in several outlets (including TechCrunch), but the story disappeared into the foggy ruins of time just as quickly as it arrived.

“Part of the reason is that we were very transparent,” Ittycheria said. “The last thing you want to do is hide information and appear like you’re misrepresenting information. We have lots of banks who put a lot of very sensitive information in our data platform; we’ve lots of other companies that have a lot of sensitive information. So for us, it’s really about making sure that our architecture is robust and sound. And this really forced us to double down. I would never claim that we’re never gonna get hacked again, but we’re doing everything in our power to ensure that it doesn’t.”

Nothing ventured

It’s not unusual for the biggest tech companies to launch their own investment vehicles, as we’ve seen through the years with Alphabet (which has several investment offshoots), Microsoft, Amazon, and Salesforce all ingratiating themselves with the startup fraternity. But a newer wave of enterprise corporate venture firms have entered the fray, too, including Slack, Workday, Twilio, Zoom, HubSpot, and Okta.

In 2022, it was MongoDB’s turn to launch such a fund, and in the two years since, MongoDB Ventures has invested in some eight companies.

“This is for us to build deeper relationships — we work in an ecosystem that consists of large companies and also small companies,” Ittycheria said. “Where we see a small company that we think could be interesting to work with, we say, ‘Hey, we want a chance to invest in you,’ so that extra value’s created. We also are the beneficiaries of creating some of that value.”

MongoDB only has a handful of people in its corporate development team that are mostly focused on the venture fund, and Ittycheria stresses that MongoDB takes a back seat with its investments. It also typically invests alongside other VCs, as it did with its inaugural investment in 2021 (predating the formal launch of its fund), when it quietly joined the likes of Insight Partners and Andreessen Horowitz in Apollo GraphQL’s $130 million Series D round. 

“We always take a minority position, we don’t take a board seat, and we don’t set the terms,” Ittycheria said. “But the reason startups are interested in us is because they want to leverage the MongoDB brand. We have thousands of people in the field, so they [startups] can leverage our distribution channels.”

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

Posted on mongodb google news. Visit mongodb google news

A lot has happened since Dev Ittycheria took the reins at MongoDB, the $26 billion database company he’s led as president and CEO since September 2014. Ittycheria has taken MongoDB to the cloud, steered it through an IPO, overseen its transition from open source, launched a venture capital arm, and grown the customer base from a few hundred to something approaching 50,000.

“When I joined the company, it wasn’t clear if people would trust us to be a truly mission-critical technology,” Ittycheria told TechCrunch. “When I joined, it was doing roughly $30 million in revenue; now we’re doing close to $2 billion.”

It hasn’t all been peaches and cream, though. Five months ago, MongoDB was hit by a security breach, which, while relatively contained, did momentarily risk its reputation in an industry where reputation is paramount.

Throw into the mix the whirlwind AI revolution that has engulfed just about every industry, and there was much to discuss when TechCrunch sat down with Ittycheria at MongoDB’s new London office, which opened in Blackfriars last year.

MongoDB’s London office.  Image Credits: Paul Sawers / TechCrunch

Vector’s embrace

Databases have come a long way since IBM and Oracle first popularized relational databases more than half a century ago. The internet’s rise created demand for flexible, scalable, and cost-effective data storage and processing, paving the way for businesses such as MongoDB to thrive.

Founded in 2007 by a trio of veterans hailing from online adtech company DoubleClick (which Google acquired for $3.1 billion), MongoDB was initially called 10Gen until a rebrand to the name of its flagship product six years later. It has since emerged as one of the preeminent NoSQL databases, helping companies store and manage large volumes of data.

Prior to joining MongoDB, Ittycheria founded and exited a server automation company called BladeLogic for $900 million in 2008, and went on to serve in various board member and investor roles (including a 16-month stint at Greylock) before joining MongoDB as president and CEO coming on for 10 years ago now. Ittycheria replaced Max Schireson, who stepped down for family reasons after just 18 months in the role.

Built on a document-oriented model, MongoDB has grown off the back of the explosion in mobile and web applications where flexible, dynamic data structures are at play. The current artificial intelligence wave is driving a similar shift, with vector databases the hot new thing in town.

Like NoSQL, vector databases also specialize in unstructured data types (e.g., images, videos, social media posts), but are particularly well suited to large language models (LLMs) and generative AI. This is due to the way they store and process data in the form of vector embeddings, which convert data into numerical representations that capture relationships between different data points by storing them spatially by relevance. This makes it easier to retrieve semantically similar data and allows AI to better understand context and semantics within conversations.

While a slew of dedicated vector database startups have emerged these past few years, the incumbents have also started embracing vector, including Elastic, Redis, OpenSearch, Cassandra, and Oracle. Cloud hyperscalers, including Microsoft, Amazon, and Google have also ramped up support for vector search.

MongoDB, for its part, introduced vector search to its flagship database-as-a-service product Atlas last June, a sign that the company was preparing for the oncoming AI tsunami. This mimics other historical trends where single-function databases emerge (such as time-series) with some utility as stand-alone solutions but that might also be better integrated into a larger multi-purpose database stack. This is precisely why MongoDB introduced support for time-series databases a few years back, and why it’s doing the same with vector.

“A lot of these companies are features masking as products,” Ittycheria said of the new wave of dedicated vector products. “We built that into the platform, and that’s the value — rather using some stand-alone vector database and then your OLTP [online transaction processing] database and then your search database, we can combine all three things into one platform that makes the life of a developer and architect so much easier.”

The idea is that database providers that adopt a multipronged approach can combine all the data in one place, making life easier for developers to work with.

“There’s probably like 17 different types of databases, and probably about 300 vendors,” Ittycheria said. “There’s no customer on this planet that wants to have 17 different databases. The complexity that creates, and the cost of learning, supporting and managing those different technologies becomes overwhelming. It also inhibits innovation, because it creates this tax of complexity.”

MongoDB’s Dev Ittycheria. Image Credits: MongoDB

Too much hype

Despite the preparation, Ittycheria reckons there is too much hype around AI — for now, at least.

“My life has not been transformed by AI,” he said. “Yes, maybe I can write an email better through all those assistants, but it’s not fundamentally transformed my life. Whereas the internet has completely transformed my life.”

The theory is that despite the hullaballoo, it will take time for AI to seep into our everyday lives — and when it does, it will be through applications integrating AI, and businesses building on it.

“I think with the adoption of any new technology, we see value accrue at the bottom layer first,” Ittycheria said. “Obviously, Nvidia is making money hand over fist, and OpenAI has been the most talked about company since they launched ChatGPT. But the real value will come when people build applications on top of those technologies. And that’s the business we’re in — we’re in the business of helping people build applications.”

For now, it’s all about “simple apps,” as Ittycheria puts it. This includes chatbots for customer service, something that MongoDB itself is doing internally with CoachGTM, powered by MongoDB’s vector search, to bring its sales and customer teams instant knowledge about their products. In some ways, we’re currently in the “calculator apps” stage that the iPhone found itself in nearly 20 years ago when the concept of the App Store hit the masses.

“The real sophisticated [AI] apps will be using real-time data, being able to make real-time decisions on real-time events,” Ittycheria said. “Maybe something’s happening in the stock market, maybe it’s time to buy or sell, or it’s time to hedge. I think that’s where we will start seeing much more sophisticated apps, where you can embed real-time data along with all the reasoning.”

The SaaS path

One of the biggest developments during Ittycheria’s tenure has been the transition from a self-deployed model, where customers host MongoDB themselves and the company sells them features and services. With the launch of Atlas in 2016, MongoDB embarked on the familiar SaaS path where companies charge for removing all the complexities of self-hosting. At the time of its IPO the following year, Atlas represented 2% of MongoDB’s revenue — today that figure sits at nearly 70%.

“It’s grown very quickly, and we’ve really built that business as a public company,” Ittycheria said. “What the popularity of Atlas showed was that people are comfortable consuming infrastructure as a service. What that allows them to do is delegate what they consider ‘non-strategic functions,’ like provisioning, configuring and managing MongoDB. So they can focus on building applications that are really transforming their business.”

Another major development came when, a year after going public, MongoDB moved away from an open source AGPL license to a source-available SSPL (server side public license). In some ways, this was the bellwether of what was to come, with countless infrastructure companies going on to abandon their open source credentials to prevent the cloud giants (e.g., Amazon) from selling their own version of the service without giving back.

“We feel very happy about it [the license change],” Ittycheria said. “The reality is that while it was open source, 99.9% of the development is done by our own people — it’s not like communities contributing code. It’s not some simple, trivial application — it’s very complex code, and we need to hire senior, talented people who cost a lot of money. We didn’t think it was fair for us to spend all this money to build this product, then someone takes that free product, monetizes it, and not give us anything back. It was quite controversial in 2018, but looking back, our business has only grown faster.”

And grown it has. As with just about every tech company, MongoDB’s valuation soared during the pandemic, peaking at an all-time high of $39 billion in late 2021, before plummeting south of $10 billion within a year — roughly the same as its pre-pandemic figure.

However, MongoDB’s shares have been in ascendency in the 18 months since, hitting $35 billion just a couple of months ago, before dropping again to around $26 billion today — such is the volatile nature of the stock markets. But given the company’s relatively modest $1.8 billion valuation at the end of its first day of trading in 2017, MongoDB has performed fairly well for public market investors.

Dev Ittycheria with MongoDB colleagues at its 2017 IPO. Image Credits: MongoDB

Four months ago, though, MongoDB revealed a data breach that exposed “some customer account metadata and contact information” — it involved a phishing attack through a third-party enterprise tool (Ittycheria wouldn’t confirm which). This caused its shares to drop 3%, but in the months that followed, MongoDB’s valuation surged back to a two-year high. This highlighted how little impact the breach had on affairs at the company, certainly compared to high-profile data breaches at the likes of Equifax and Target, which hit the businesses hard and forced senior executive departures.

While MongoDB’s cybersecurity incident was significantly smaller in scope, what stood out was how quickly the whole thing went away — it was reported in several outlets (including TechCrunch), but the story disappeared into the foggy ruins of time just as quickly as it arrived.

“Part of the reason is that we were very transparent,” Ittycheria said. “The last thing you want to do is hide information and appear like you’re misrepresenting information. We have lots of banks who put a lot of very sensitive information in our data platform; we’ve lots of other companies that have a lot of sensitive information. So for us, it’s really about making sure that our architecture is robust and sound. And this really forced us to double down. I would never claim that we’re never gonna get hacked again, but we’re doing everything in our power to ensure that it doesn’t.”

Nothing ventured

It’s not unusual for the biggest tech companies to launch their own investment vehicles, as we’ve seen through the years with Alphabet (which has several investment offshoots), Microsoft, Amazon, and Salesforce all ingratiating themselves with the startup fraternity. But a newer wave of enterprise corporate venture firms have entered the fray, too, including Slack, Workday, Twilio, Zoom, HubSpot, and Okta.

In 2022, it was MongoDB’s turn to launch such a fund, and in the two years since, MongoDB Ventures has invested in some eight companies.

“This is for us to build deeper relationships — we work in an ecosystem that consists of large companies and also small companies,” Ittycheria said. “Where we see a small company that we think could be interesting to work with, we say, ‘Hey, we want a chance to invest in you,’ so that extra value’s created. We also are the beneficiaries of creating some of that value.”

MongoDB only has a handful of people in its corporate development team that are mostly focused on the venture fund, and Ittycheria stresses that MongoDB takes a back seat with its investments. It also typically invests alongside other VCs, as it did with its inaugural investment in 2021 (predating the formal launch of its fund), when it quietly joined the likes of Insight Partners and Andreessen Horowitz in Apollo GraphQL’s $130 million Series D round. 

“We always take a minority position, we don’t take a board seat, and we don’t set the terms,” Ittycheria said. “But the reason startups are interested in us is because they want to leverage the MongoDB brand. We have thousands of people in the field, so they [startups] can leverage our distribution channels.”

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

Posted on mongodb google news. Visit mongodb google news

Cwm LLC lifted its position in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) by 3.4% during the fourth quarter, Holdings Channel.com reports. The firm owned 2,680 shares of the company’s stock after purchasing an additional 89 shares during the period. Cwm LLC’s holdings in MongoDB were worth $1,096,000 as of its most recent SEC filing.

Other institutional investors also recently modified their holdings of the company. Blue Trust Inc. raised its position in shares of MongoDB by 937.5% during the fourth quarter. Blue Trust Inc. now owns 83 shares of the company’s stock worth $34,000 after purchasing an additional 75 shares during the period. BluePath Capital Management LLC purchased a new stake in MongoDB in the 3rd quarter valued at $30,000. AM Squared Ltd purchased a new stake in MongoDB in the 3rd quarter valued at $35,000. Cullen Frost Bankers Inc. purchased a new stake in MongoDB in the 3rd quarter valued at $35,000. Finally, Castleview Partners LLC purchased a new stake in MongoDB in the 3rd quarter valued at $37,000. 89.29% of the stock is owned by institutional investors and hedge funds.

MongoDB Stock Performance

NASDAQ:MDB opened at $383.80 on Friday. MongoDB, Inc. has a 52-week low of $215.56 and a 52-week high of $509.62. The company has a debt-to-equity ratio of 1.07, a quick ratio of 4.40 and a current ratio of 4.40. The stock has a 50-day simple moving average of $379.60 and a two-hundred day simple moving average of $390.90. The firm has a market capitalization of $27.95 billion, a PE ratio of -154.76 and a beta of 1.19.

MongoDB (NASDAQ:MDB – Get Free Report) last issued its quarterly earnings data on Thursday, March 7th. The company reported ($1.03) earnings per share (EPS) for the quarter, missing analysts’ consensus estimates of ($0.71) by ($0.32). MongoDB had a negative net margin of 10.49% and a negative return on equity of 16.22%. The company had revenue of $458.00 million for the quarter, compared to analysts’ expectations of $431.99 million. Analysts forecast that MongoDB, Inc. will post -2.53 EPS for the current year.

Wall Street Analysts Forecast Growth

A number of equities research analysts recently commented on the company. Tigress Financial increased their price target on MongoDB from $495.00 to $500.00 and gave the company a “buy” rating in a research report on Thursday, March 28th. Needham & Company LLC reaffirmed a “buy” rating and issued a $465.00 price target on shares of MongoDB in a report on Thursday. Stifel Nicolaus reaffirmed a “buy” rating and issued a $435.00 price target on shares of MongoDB in a report on Thursday, March 14th. UBS Group reissued a “neutral” rating and set a $410.00 price objective (down from $475.00) on shares of MongoDB in a report on Thursday, January 4th. Finally, Loop Capital initiated coverage on MongoDB in a report on Tuesday, April 23rd. They set a “buy” rating and a $415.00 price objective on the stock. Two research analysts have rated the stock with a sell rating, three have given a hold rating and twenty have given a buy rating to the company’s stock. According to MarketBeat.com, MongoDB has an average rating of “Moderate Buy” and an average price target of $443.86.

Read Our Latest Stock Analysis on MongoDB

Insider Transactions at MongoDB

In other news, CRO Cedric Pech sold 1,430 shares of the stock in a transaction that occurred on Tuesday, April 2nd. The stock was sold at an average price of $348.11, for a total value of $497,797.30. Following the sale, the executive now directly owns 45,444 shares in the company, valued at $15,819,510.84. The sale was disclosed in a document filed with the SEC, which is available at this link. In related news, CAO Thomas Bull sold 170 shares of the stock in a transaction that occurred on Tuesday, April 2nd. The stock was sold at an average price of $348.12, for a total value of $59,180.40. Following the transaction, the chief accounting officer now owns 17,360 shares of the company’s stock, valued at $6,043,363.20. The sale was disclosed in a legal filing with the SEC, which can be accessed through the SEC website. Also, CRO Cedric Pech sold 1,430 shares of the stock in a transaction that occurred on Tuesday, April 2nd. The stock was sold at an average price of $348.11, for a total value of $497,797.30. Following the completion of the transaction, the executive now directly owns 45,444 shares in the company, valued at approximately $15,819,510.84. The disclosure for this sale can be found here. Over the last three months, insiders have sold 91,802 shares of company stock worth $35,936,911. 4.80% of the stock is currently owned by company insiders.

MongoDB Profile

(Free Report)

MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides 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-premises, 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.

Recommended Stories

Want to see what other hedge funds are holding MDB? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for MongoDB, Inc. (NASDAQ:MDB – Free Report).

Receive News & Ratings for MongoDB Daily – Enter your email address below to receive a concise daily summary of the latest news and analysts’ ratings for MongoDB and related companies with MarketBeat.com’s FREE daily email newsletter.

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

Posted on mongodb google news. Visit mongodb google news

MongoDB, Inc. (NASDAQ:MDB – Get Free Report)’s stock price gapped up before the market opened on Friday . The stock had previously closed at $366.13, but opened at $382.44. MongoDB shares last traded at $380.18, with a volume of 333,939 shares trading hands.

Analyst Ratings Changes

A number of equities analysts recently issued reports on MDB shares. Citigroup increased their price objective on MongoDB from $515.00 to $550.00 and gave the stock a “buy” rating in a report on Wednesday, March 6th. KeyCorp decreased their price objective on MongoDB from $490.00 to $440.00 and set an “overweight” rating for the company in a report on Thursday, April 18th. Loop Capital started coverage on MongoDB in a report on Tuesday, April 23rd. They issued a “buy” rating and a $415.00 price objective for the company. Truist Financial increased their price objective on MongoDB from $440.00 to $500.00 and gave the stock a “buy” rating in a report on Tuesday, February 20th. Finally, Redburn Atlantic restated a “sell” rating and issued a $295.00 target price (down from $410.00) on shares of MongoDB in a research report on Tuesday, March 19th. Two equities research analysts have rated the stock with a sell rating, three have assigned a hold rating and twenty have assigned a buy rating to the company’s stock. According to MarketBeat, MongoDB presently has a consensus rating of “Moderate Buy” and an average target price of $443.86.

View Our Latest Report on MDB

MongoDB Price Performance

The business has a 50-day moving average price of $379.60 and a 200 day moving average price of $390.90. The company has a market cap of $27.95 billion, a price-to-earnings ratio of -154.76 and a beta of 1.19. The company has a current ratio of 4.40, a quick ratio of 4.40 and a debt-to-equity ratio of 1.07.

MongoDB (NASDAQ:MDB – Get Free Report) last released its earnings results on Thursday, March 7th. The company reported ($1.03) earnings per share (EPS) for the quarter, missing analysts’ consensus estimates of ($0.71) by ($0.32). The business had revenue of $458.00 million during the quarter, compared to analysts’ expectations of $431.99 million. MongoDB had a negative net margin of 10.49% and a negative return on equity of 16.22%. As a group, research analysts expect that MongoDB, Inc. will post -2.53 earnings per share for the current fiscal year.

Insider Activity

In other news, Director Dwight A. Merriman sold 2,000 shares of the company’s stock in a transaction on Monday, April 8th. The shares were sold at an average price of $365.00, for a total value of $730,000.00. Following the transaction, the director now directly owns 1,154,784 shares of the company’s stock, valued at $421,496,160. The transaction was disclosed in a document filed with the Securities & Exchange Commission, which is available at this hyperlink. In other news, Director Dwight A. Merriman sold 2,000 shares of the company’s stock in a transaction on Monday, April 8th. The shares were sold at an average price of $365.00, for a total value of $730,000.00. Following the transaction, the director now directly owns 1,154,784 shares of the company’s stock, valued at $421,496,160. The transaction was disclosed in a document filed with the Securities & Exchange Commission, which is available at this hyperlink. Also, CAO Thomas Bull sold 170 shares of the company’s stock in a transaction on Tuesday, April 2nd. The stock was sold at an average price of $348.12, for a total transaction of $59,180.40. Following the completion of the transaction, the chief accounting officer now directly owns 17,360 shares in the company, valued at $6,043,363.20. The disclosure for this sale can be found here. Insiders sold 91,802 shares of company stock worth $35,936,911 over the last quarter. Corporate insiders own 4.80% of the company’s stock.

Hedge Funds Weigh In On MongoDB

A number of hedge funds have recently modified their holdings of the stock. Exchange Traded Concepts LLC increased its position in MongoDB by 74.7% during the third quarter. Exchange Traded Concepts LLC now owns 3,370 shares of the company’s stock worth $1,166,000 after buying an additional 1,441 shares during the last quarter. Oak Thistle LLC acquired a new position in MongoDB during the third quarter worth $259,000. Handelsbanken Fonder AB increased its position in MongoDB by 1.0% during the third quarter. Handelsbanken Fonder AB now owns 33,735 shares of the company’s stock worth $11,668,000 after buying an additional 346 shares during the last quarter. Fjarde AP Fonden Fourth Swedish National Pension Fund increased its position in MongoDB by 1.3% during the third quarter. Fjarde AP Fonden Fourth Swedish National Pension Fund now owns 15,100 shares of the company’s stock worth $5,222,000 after buying an additional 200 shares during the last quarter. Finally, Accurate Wealth Management LLC acquired a new position in MongoDB during the third quarter worth $251,000. 89.29% of the stock is owned by institutional investors and hedge funds.

MongoDB Company Profile

(Get Free Report)

MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides 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-premises, 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.

Featured Stories

Receive News & Ratings for MongoDB Daily – Enter your email address below to receive a concise daily summary of the latest news and analysts’ ratings for MongoDB and related companies with MarketBeat.com’s FREE daily email newsletter.

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