Month: June 2023

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With the Fed not quite committing yet to lowering or even pausing interest rate hikes, many investors are wondering if the sharp rally that we’ve seen in the markets since the start of May can be sustained. The gains have been especially notable in tech stocks, which shook off a very weak second half of 2022 to rebound.

MongoDB (NASDAQ:MDB), in particular, has nearly clawed its way back to 2022 levels. Up more than 100% year to date, the gains started accelerating in June as MongoDB reported excellent Q1 results. The question for investors now is: can the rally keep going?

I made a fortunate bullish call on MongoDB at the start of this year that has, needless to say, paid off handsomely. It’s tempting to look at the strength of MongoDB’s price chart over the past two months and say the stock has reached a cliff, but now is not the right time to be greedy – especially with so much uncertainty over interest rates. Owing primarily to valuation, I’m pivoting to neutral on MongoDB and locking in the gains on my trade.

It would be remiss not to acknowledge the fact that MongoDB is still a fantastic company, fundamentally speaking. I still see a number of tailwinds driving the bull case for MongoDB:

• Growth at scale. Very few companies that have reached a >$1 billion annual run rate are still growing revenue north of >50% y/y, and MongoDB is one of those few. That’s a testament to the all-encompassing, horizontal nature of MongoDB’s product. Almost all companies now have a use for managing unstructured data, and its technology is broadly applicable across a wide variety of use cases.

• Secular tailwinds. More and more these days, companies and brand marketers want to capture consumer data coming from “unstructured” sources – Tweets, social media posts, and the like. Traditional databases which store data in a columnar format are not equipped to handle this. MongoDB’s generous growth rates are a reflection of the largesse of the company’s space.

At the same time, however, at higher prices I’m more cognizant of several risks:

• GAAP losses are still large. Though MongoDB has notched positive pro forma operating and net income levels, the company is still burning through large GAAP losses because of its reliance on stock-based compensation. In boom times investors may look the other way, but in this more cautious market environment MongoDB’s losses may stand out.
• Competition. MongoDB may have called itself an “Oracle killer” at the time of its IPO, but Oracle (ORCL) is also making headway in autonomous and non-relational databases. Given Oracle’s much broader software platform and ease of cross-selling, this may eventually cut into MongoDB’s momentum.

The biggest thing we have to watch out for, however, is MongoDB’s enormous valuation. At current share prices near $390, MongoDB trades at a market cap of $27.33 billion. After we net off the $1.90 billion of cash and $1.14 billion of convertible debt on MongoDB’s most recent balance sheet, the company’s resulting enterprise value is $26.57 billion.

Meanwhile, for the current fiscal year MongoDB has guided to $1.522-$1.542 billion in revenue, representing 19-20% y/y growth:

Taking even the high end of this guidance range at face value (as MongoDB has had an unbroken tendency to “beat and raise”), the stock’s valuation stands at 17.2x EV/FY24 revenue. Let’s not even mention that from a P/E basis (though as EPS growth is still in its nascent stages, this isn’t an entirely fair valuation either) MongoDB is trading at a >200x P/E ratio.

The bottom line here: I view MongoDB as one of the few tech stocks to have returned very close to pandemic-era mania levels. While I can’t argue that the company’s fundamentals and market opportunity is very strong in a vacuum, it’s difficult to see any further upside at MongoDB’s high-teens revenue multiple.

Q1 download

Let’s now go through MongoDB’s latest quarterly results in greater detail. The Q1 earnings summary is shown below:

MongoDB’s revenue grew 29% y/y to $368.3 million, beating Wall Street’s expectations of $347.1 million (+22% y/y) by a seven-point margin, but also decelerating seven points from Q4’s growth rate of 36% y/y. Subscription revenue also grew at 29% y/y, while the smaller slice of professional services revenue grew 25% y/y.

Where MongoDB also exceeded expectations was on net customer adds, adding 2.3k net-new customers in the quarter to end with 43.1k total customers. As the company has focused more on its direct-sales business, it has been able to bring in a wider net of smaller self-service customers. That being said, MongoDB also added 110 net-new customers with greater than $100k in ARR, up 28% y/y.

Management noted that customer consumption trends are above expectations, driven by higher-than-expected underlying application usage. That being said, consumption growth levels are still lower than where they were when MongoDB entered into the macro-driven slowdown in Q2 of last year. Net ARR expansion rates were 120%, indicating that a typical installed base customer spends 20% more in the following year.

Additional investor enthusiasm poured into MongoDB as the company highlighted that customers are choosing the MongoDB platform to build and deploy AI-driven applications. Per CEO Dev Ittycheria’s remarks on the Q1 earnings call:

Moreover, the shift to AI will favor modern platforms that offer a rich and sophisticated set of capabilities, delivered in a performance and scalable way. We are observing an emerging trend where customers are increasingly choosing Atlas as a platform to build and run new AI applications. For example, in Q1, more than 200 of the new Atlas customers were AI or ML companies. Well finance startups like Hugging Face, Tekion, One AI are examples of companies using MongoDB to help deliver the next wave of AI-powered applications to their customers. We also believe that many existing applications will be re-platformed to be AI-enabled. This will be a compelling reason for customers to migrate from legacy technologies to MongoDB.

To summarize, AI is just the latest example of the technology that promises to accelerate the production of more applications and greater demand for operational data stores, especially the ones best suited for modern data requirements such as MongoDB.

From a profitability standpoint, MongoDB’s pro forma gross margins lifted one point y/y to 76%. Pro forma operating margins clocked in at 12%, six points richer than 6% in the year-ago Q1.

Key takeaways

In my view, the ~2x gain in MongoDB since the start of the year has been a generous run. Yes, a good chunk of that is justified by fundamentals as MongoDB continues on a path of ~30% y/y growth alongside substantial margin expansion, fueled by potential further tailwinds from AI workloads migrating onto the platform – but it’s difficult to justify a ~17x forward revenue multiple. Retreat to the sidelines here.

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Article originally posted on InfoQ. Visit InfoQ

The Microsoft security team recently released AzDetectSuite, a collection of KQL queries and detection alerts against security threads on Azure and AzureAD. The open-source project provides basic detection capabilities at a low cost, targeting small environments within the Microsoft cloud platform.

AzDetectSuite is an open-source library designed to help developers detect and understand tactics, techniques, and procedures used in cyber-attacks on Azure networks.

Written to match the Azure Threat Research Matrix (ATRM), a knowledge base built to document known TTPs within Azure and Azure AD, the detections are grouped according to the different tactics involved: reconnaissance, initial access, execution, privilege escalation, persistence, credential access, and exfiltration. Ryan Hausknecht, senior security researcher at Microsoft, explains:

AzDetectSuite is a project created to allow Azure users to establish a basic defense within Azure by giving pre-built KQL queries for each technique within ATRM that are deployable Alerts to Azure Monitor. In ATRM, most (85%+) techniques will have a KQL query and a button that will deploy the query to their Azure subscription.

For example, AzDetectSuite supports detections for attacks like Azure Key Vault dumping, account creation or manipulation, or password spraying. The detections are written using the Kusto Query Language (KQL), a language designed to explore data and discover patterns, identify anomalies and outliers, and create statistical modeling.

The new library relies on Azure Monitor, the centralized service that ingests data from different log sources, including general Azure Log (AzureActivity) and more detailed logs, such as Service Principal Sign-Ins (AADServicePrincipalSignInLogs).

AzDetectSuite is not the main option available for TTPs on Azure and AzureAD. Hausknecht warns:

AzDetectSuite (ADS) is not meant to compete with Microsoft Defender for Cloud (MDC). MDC provides advanced detections based on your subscription plan and will give more granular control based on the telemetry in a tenant. ADS is meant to be an open-source suite of basic detections for techniques found within ATRM.

The announcement explains how to build alerts for anomalous behaviors and how to handle baselining in KQL. On Twitter, Hausknecht adds:

The goal of this is to continue releasing OSS tooling that will benefit Azure users. It definitely goes against some of the mentality I’ve come across internally, but I’m firm in my belief that people should be able to have a security baseline for free.

The project’s GitHub repository contains the KQL queries and the PowerShell script Invoke-AzDetectSuite.ps1 to import detections for all or specific tactics. The detections are available for free but customers might still be charged for alert fees.

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On June 26, 2023, the options scanner of a leading financial news outlet detected 15 unusual options trades for MongoDB. The traders who made these trades were divided in their sentiment, with 26% being bullish and 73% bearish. The options uncovered included 6 puts, worth $303,072 in total, and 9 calls, worth $605,197 in total. These trades suggest that large investors, or “whales,” have been targeting a price range of $70.0 to $650.0 for MongoDB over the last three months.

In other news, Capital One recently initiated coverage of MongoDB with an Equal-Weight recommendation on June 26, 2023. The average one-year price target for the company, as of June 2, 2023, is $266.84, with forecasts ranging from $181.80 to $383.25. This represents a decrease of 31.58% from the latest reported closing price of $389.99.

Meanwhile, Victory Capital Management Inc. has reduced its stake in MongoDB by 50.9% during the fourth quarter. As of June 21, 2023, the stock is trading at $371.25, a drop of $8.53 or 2.25% from the previous closing.

MDB Stock Analysis: Significant Increase in Earnings and Revenue Growth in 2023

On June 26, 2023, MDB stock opened at $388.00, up from the previous day’s close of $379.85. Throughout the day, the stock’s range fluctuated between $375.31 and $393.60, with a volume of 78,699 shares traded.

MDB has a market capitalization of $27.5 billion, and its earnings growth over the past year has been -5.89%. However, the company has seen a significant increase in earnings growth this year, with a growth rate of +92.12%. Over the next five years, the company is expected to see a steady growth rate of +8.00%.

In terms of revenue growth, MDB has seen a significant increase of +46.95% over the past year. The company’s P/E ratio is not available, but its price/sales ratio is 11.45, and its price/book ratio is 36.88.

MDB’s next reporting date is August 31, 2023, with an EPS forecast of $0.46 for this quarter.

Overall, MDB has seen a significant increase in earnings growth this year and revenue growth over the past year. However, its net profit margin remains negative, and the company’s stock price experienced significant fluctuations throughout the day. Investors should continue to monitor the company’s financial performance and market trends to make informed investment decisions.

MongoDB Incs Stock Shows Bullish Sentiment with Strong Financial Performance and Growth Prospects

On June 26, 2023, MongoDB Inc (MDB) was trading at a price of 379.85. The 22 analysts offering 12-month price forecasts for the company had a median target of 420.50, with a high estimate of 445.00 and a low estimate of 210.00. The current consensus among 27 polled investment analysts was to buy stock in MongoDB Inc. The company had reported earnings per share of $0.46 in the current quarter, with sales of $393.9M. The bullish sentiment was driven by the company’s strong financial performance and growth prospects.

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

Posted on mongodb google news. Visit mongodb google news

The developer-led data platform isn’t new at MongoDB Inc., but what is new is the advent of artificial intelligence — something that led the company to spring to action.

But in some ways, the company’s developer data platform was “prescient,” according to Mindy Lieberman (pictured, right), chief information officer of MongoDB. 

“It’s all about data, and applications on top of data,” she said. “I look at it, for IT, as a portfolio. There’s some that is built; there is some that is bought. When you can’t go to the market and find things that are fit for purpose, you have to build. And to have a developer platform available, and I get good pricing, that can’t be beat.”

Lieberman and Tara Hernandez (left), vice president of developer productivity at MongoDB, spoke with theCUBE industry analyst John Furrier at the MongoDB .local NYC event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how to approach security, the role of AI and how developers are driving things forward. (* Disclosure below.)

Data in everything

These days, data is ubiquitous across entire enterprises, and companies need to be careful about how they manage it, according to Lieberman.

“You have to figure out ways to gather [data], to disseminate it, to cleanse it. So it’s all about the data,” she said.

On the developer side of things, whether it comes to testing or analysis, it’s critical to be mindful of how customer data is managed and how to build guardrails so developers aren’t looking at anything they aren’t supposed to, according to Hernandez. That also goes for ensuring that data is saved in a safe way, without getting in the way.

“That’s what DevSecOps is. That idea of a shift left is interesting, not because it’s making the develops more acutely aware of security — I mean, that’s a little part of it — but it’s that we ideally have created a platform where they don’t have to worry about it,” Hernandez said. “But they get the benefit of the protections that were built into how they do their development.”

Open-source has proven that developers are driving the bus. So, what are the operations good enough to enable developers and not foreclose them from being curious, experimental and playful with code? Aside from providing developer tooling to experiment with and figure out what works versus what is hype, MongoDB’s goal is focused on collaboration and a “very light touch” on coordination, according to Lieberman.

“Basically, we are saying yes to safe cases. We are trying to shorten the process to make sure that people can get their hands on things early and often. We test, and learn, and then expand,” she said.

MongoDB is based on open-source technology at its heart, which enables people to grab the community build or go to GitHub to grab the source, according to Hernandez. That applies to technology like ChatGPT too.

“One of the first things we said is, we took a quick pass and like, ‘You want to play with ChatGPT?’” Hernandez said. “Point it at the public repos, because the guardrail is already public.”

The internal stuff can be worked on as fast as possible, but there’s no reason that the company couldn’t have a reasonable set of policies to get started, Hernandez added.

Here’s the complete video interview with Mindy Lieberman and Tara Hernandez, part of SiliconANGLE’s and theCUBE’s coverage of the MongoDB .local NYC event:

(* Disclosure: TheCUBE is a paid media partner for the MongoDB .local NYC event. Neither MongoDB Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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

Posted on mongodb google news. Visit mongodb google news

Enterprise Database Management Suite Market is growing at a +6% CAGR during the forecast period 2023-2030. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market

An enterprise database management suite is a suite of software tools used to manage a large collection of databases in an enterprise. It typically includes database management systems, data integration and transformation tools, query and reporting tools, database security and access control tools, and data warehouse and analytics tools. Enterprise database management suites provide a single unified platform for managing complex and large data stores and may also include application development, database maintenance, and data analytics and visualization features.

Get the PDF Sample Copy (Including FULL TOC, Graphs and Tables) of this report @: https://www.researchcognizance.com/sample-request/212980

Enterprise Database Management Suite market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis.

Top Companies of this Market includes: Oracle, Microsoft, IBM, SAP, AWS, MongoDB, Google, Broadcom, MarkLogic, MariaDB, InterSystems, Cloudera, Teradata, Vertica, Alibaba Cloud, Knack

This report provides a detailed and analytical look at the various companies that are working to achieve a high market share in the global Enterprise Database Management Suite market. Data is provided for the top and fastest growing segments. This report implements a balanced mix of primary and secondary research methodologies for analysis. Markets are categorized according to key criteria. To this end, the report includes a section dedicated to the company profile. This report will help you identify your needs, discover problem areas, discover better opportunities, and help all your organization’s primary leadership processes. You can ensure the performance of your public relations efforts and monitor customer objections to stay one step ahead and limit losses.

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Market Penetration: Comprehensive information on the product portfolios of the top players in the Enterprise Database Management Suite market.

Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market.

Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market.

Market Development: Comprehensive information about emerging markets. This report analyzes the market for various segments across geographies.

Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Enterprise Database Management Suite market.

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The cost analysis of the Global Enterprise Database Management Suite Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.

Global Enterprise Database Management Suite Market Segmentation:

Market Segmentation by Type:

• Relational Database
• Nonrelational Database

Market Segmentation by Application:

• SMEs
• Large Enterprise

Reasons for buying this report:

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• It offers massive data about trending factors that will influence the progress of the Enterprise Database Management Suite

Table of Contents

Global Enterprise Database Management Suite Market Research Report 2023

Chapter 1 Enterprise Database Management Suite Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Enterprise Database Management Suite Market Forecast

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

Posted on mongodb google news. Visit mongodb google news

It’s been another busy week for theCUBE, SiliconANGLE Media’s livestreaming studio, with industry analysts Dave Vellante and John Furrier providing exclusive insights from HPE Discover and MongoDB .local NYC.

TheCUBE’s event coverage won’t slow down in the coming weeks, with Snowflake Summit in Las Vegas and the Data + AI Summit in San Francisco, kicking off this week. Through all of this, artificial intelligence continues to drive a lot of hype and is a key area of focus at this summer’s tech events.

“It’s a big week coming up. We’ve got Snowflake and Databricks, and a slew of interviews,” Furrier said on the latest episode of theCUBE podcast. “I think we’re going to be talking to at least 100 companies in the next week. And last week felt like 100, as well, Dave. It’s just been an incredible week.”

Views on MongoDB Atlas

During MongoDB .local NYC, MongoDB announced that it would be beefing up its cloud database MongoDB Atlas with a series of new products and features.

“That Atlas Vector Search is really interesting, because it’s an alternative to having a separate standalone vector database, and obviously that is something that is going to be interesting for generative AI,” Vellante said.

The company also surprised many people with stream processing for Atlas, while making general availability of the relational migrator, according to Vellante. The event has led to “major bullish sentiment” on MongoDB, according to Furrier.

“Category creation opportunity for them. Clear headroom in the [total addressable market] of a database market that they only have 2% of, and the database market is changing and growing,” Furrier said. “So, you have a huge TAM in databases and a changing market in how developers are setting the agenda for buying decisions.”

The theme, then, is that MongoDB owns the dorm room hackathons, which then go into the boardrooms where the checks are written, according to Furrier.

On a previous episode of theCUBE podcast, Furrier and Vellante discussed MongoDB’s stock soaring in the wake of blowout fiscal first-quarter earnings results.

Since day one, theCUBE has been covering open source, which continues to surprise and delight in terms of what’s going on in the marketplace, according to Furrier.

“They have operating leverage in their model, because they have a platform now. And they have the developers, so they’re growing with their developers,” Furrier said. “Because what’s happening is, anyone can use MongoDB.”

Structural changes in view

In 2019, Hewlett Packard Enterprise Co. Chief Executive Officer Antonio Neri made a commitment to deliver HPE’s entire portfolio as-a-service, something that has definitely succeeded, according to Furrier. The company has partnered with the public cloud to operationalize hybrid cloud as a service, something that is a moneymaker.

HPE wants to optimize for product groups because it gets profit and loss and has objects to hit, according to Vellante.

“But doing what’s best for that individual P&L might not be what’s best for the overall company. So, Antonio has had to get people in a little bit of a headlock, and the key has been Aruba,” Vellante said. “That acquisition, we talked about this on theCUBE the other day, has been a home run.”

HPE uses Aruba Central for the console for GreenLake and is bringing the Aruba IP into the storage business. It has also put Tom Black, who has been involved with Aruba, in charge of the storage business. It has been interesting to see the networking and security coming together, much as it has at Cisco Systems Inc., according to Vellante.

“Then the other big news at HPE Discover was LLMs as a service. We just had Rob Strechay and Andy Thurai here, we were unpacking that,” Vellante said. “I think there was a little skepticism there. But I liked the play.”

Neri is “ballsy” in saying that he’s not going to put his supercomputing IP in the public cloud, according to Vellante. Instead, he said he’s going to take a shot and build his own public cloud, something that Vellante liked.

“It’s a little Oracle-like. Unfortunately, they don’t have the software stack and the application stack … in the database that Oracle has,” he said. “But for an infrastructure company, they’ve got to do things that differentiate, because unlike Dell, they can’t just go volume and have mega supply chain.”

Watch the full theCUBE Podcast below to find out why these industry pros were also mentioned:

Mark Zuckerberg, CEO of Meta Platforms Inc.

Elon Musk, CEO of Tesla Inc.

Daniel Newman, CEO at The Futurum Group and chief analyst at Futurum Research

Maribel Lopez, founder and principal analyst at Lopez Research

Ivana Delevska, founder and chief investment officer at Spear Invest

Cathie Wood, founder and CEO at ARK Investment Management LLC

Adam Selipsky, CEO of Amazon Web Services Inc.

Matt Garman, SVP of sales and marketing at AWS

George Gilbert, principal at TechAlpha Partners

Sanjeev Mohan, principal at SanjMo

Doug Henschen, vice president and principal analyst at Constellation Research Inc.

Antonio Neri, president and CEO of Hewlett Packard Enterprise Co.

Matt Wood, vice president of analytics, business intelligence and machine learning at Amazon Web Services Inc.

Tom Black, executive vice president and general manager of storage at HPE Co.

Jayshree Ullal, CEO and president of Arista Networks Inc.

Phil Mottram, EVP and GM of Aruba Networking at HPE

Andy Thurai, VP and principal analyst at Constellation Research

Stephen Orban, VP of migrations of Google Cloud at Alphabet Inc.

Larry Ellison, chairman of the board and CTO at Oracle Corp.

Jerry Chen, general partner at Greylock Partners

Charles Fitzgerald, consultative strategist and investor

David Floyer, chief technology officer and co-founder of Wikibon

Pat Gelsinger, CEO of Intel Corp.

Sarbjeet Johal, technology analyst and principal research officer

Crawford Del Prete, president of International Data Corp.

Andy Grove, former Intel CEO and president

Lina Khan, chair of the Federal Trade Commission

Bill Gates, co-founder of Microsoft Corp.

Janet Reno, former U.S. attorney general

Steve Ballmer, former CEO and president of Microsoft

Satya Nadella, chairman and CEO of Microsoft

Don’t miss out on the latest episodes of “theCUBE Podcast”! Join us by subscribing to our RSS feed. You can also listen to us on Apple Podcasts or on Spotify. And for those who prefer to watch, check out our YouTube playlist. Don’t wait any longer — tune in now and be part of the conversation!

Photo: SiliconANGLE

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

Posted on mongodb google news. Visit mongodb google news

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Artificial intelligence, including the most popular form at the moment, generative AI such as OpenAI’s ChatGPT, is going to provide tremendous leverage to software developers and make them vastly more productive, according to the chief technologist of MongoDB, the document database maker. 

“One of the things that I strongly believe is that there’s all this hype out there about how generative AI may put developers out of business, and I think that’s wrong,” said Mark Porter, MongoDB’s CTO, in an interview with ZDNET.

Also: More developers are coding with AI than you think 

“What generative AI is doing is helping us with code, helping us with test cases, helping us with finding bugs in our code, helping us with looking up documentation faster,” said Porter.

“It’s gonna let developers write code at the quality and the speed and the completeness that we’ve always wanted to.”

Not just generative AI, said Porter, “but models and all the other stuff that’s been around for 15 to 20 years that’s now really solid” will mean that “we can do things which transform how developers write code.”

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Porter met with ZDNET last week during MongoDB.local, the company’s developer conference in New York. The conference is one of 29 such developer events MongoDB is hosting this year in various cities in the US and abroad. 

Prior to becoming CTO of MongoDB three and a half years ago, Porter held numerous key database roles, including running relational database operations for Amazon AWS RDS, running core technology development as CTO at Grab, the Southeast Asia ride-hailing service, and over a decade in numerous roles at Oracle, including a stint as one of the original database kernel developers. 

AI is “an acceleration of the developer ecosystem,” added Porter. “I think more apps are going to be written.”

Also: Serving Generative AI just got a lot easier with OctoML’s OctoAI

“There’s this stereotype of how long it takes to write computer software and how long it takes to get it right,” said Porter. “I think generative AI is going change all that in massive ways, where we’re going to be able to write the apps we want to write at the speed we want to write them, at the quality we want to have them written.”

A big element of MongoDB’s one-day event was the company’s discussion of new AI capabilities for the MongoDB database. 

“MongoDB is actually the foundation of hundreds of companies building AI,” said Porter. Indeed, the show floor, at Jacob Javits convention center in Manhattan, featured numerous booths from the likes of Confluent, Hashicorp, IBM, and Amazon AWS, where presenters explained the use of MongoDB with their respective software technologies. 

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Porter emphasized new functionality in MongoDB that incorporates vector values as a native data type of the database. By supporting vectors, a developer can take the context vectors produced by the large language model, which represent an approximate answer to a query, store them in the database, and then retrieve them later using relevance searches that produce a precise answer with the necessary recall parameters. 

Also: AMD unveils MI300x AI chip as ‘generative AI accelerator’

When a user asks ChatGPT or another LLM a question, explained Porter, “I’m going to get a vector of that question, and then I’m going to put that vector into my database, and I’m then going to ask for vectors near it,” which will produce a set of relevant articles, for example. 

“Then I’m going to take those articles and prompt my LLM with all those articles, and I’m going to say, you may not say anything that is not in these articles, please answer this question with these articles.”

The LLM can then perform functions such as summarizing a long article, offered Porter. “I love to use LLMs to take an article and make it shorter.”

In that way, AI and the database have a division of labor. 

Also: Microsoft unveils Fabric analytics program, OneLake data lake to span cloud providers

“You would never want to put an LLM in an online transaction processing system,” said Porter. “I think you want to use the LLMs where they belong, and you want to use database technology and matrix technology where it belongs.”

While there are standalone vector databases from other vendors, Porter told ZDNET that incorporating the functionality will reduce the burden for application developers. “It means that you don’t have to have pipelines between the two [databases], copying data around,” said Porter, “You don’t have to manage two different systems, it’s all in one system, your core data, your metadata, and your vectors all sit in one data store.”

No matter what comes next with AI, said Porter, “It ain’t going to put developers out of business. 

“Developers are still going to be the ones who listen to their customers, listen to their leaders, and decide what to write.” 

Also: These are my 5 favorite AI tools for work

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