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MongdoDB unveiled a slew of updates for its Atlas developer platform, including integrations with AWS and Google Cloud AI tools
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The company thinks data is the key to AI acceleration
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It also wants to connect enterprises with the right AI partners via its MAAP approach
MongoDB thinks it holds the key that will let enterprises rev their artificial intelligence (AI) engines: data.
At its MongoDB.local NYC conference this week, the company unveiled a slew of updates designed to supercharge the development of artificial intelligence applications.
Among other things, it announced it is working with Google Cloud to integrate MongoDB knowledge into the latter’s Gemini Code Assist tool for developers; updated its MongoDB Atlas application development platform to enable the use of real-time streaming data with Stream Processing; topped up distributed application capabilities with Edge Server; and announced its MongoDB Atlas vector search capabilities are now generally available on Knowledge Bases for Amazon Bedrock.
That last announcement will essentially make it easier for developers to build retrieval augmented generation applications on Bedrock using specific enterprise data from MongoDB Atlas.
All of these announcements are part of a plan to allow enterprises to leverage data stored in MongoDB for AI development.
On a pre-brief call with journalists, MongoDB VP of Product Marketing and Strategy Scott Sanchez said the company essentially sees itself sitting at the center of the AI technology stack.
“Another way to think about it is sort of like bookends, with the GPUs and the models on one side and the apps on the other side. But just buying and investing in bookends without any books is pretty pointless, and that’s the data in the middle,” he said. “The importance of data has risen exponentially with this shift towards AI.”
“AI is really data hungry, but the data that feeds these models and helps with the inference is constantly changing,” he continued. “So, these sophisticated AI models really benefit from having a unified picture of your data.”
That’s exactly what MongoDB thinks it offers with Atlas. Launched in 2016, Sanchez said Atlas is used by nearly 50,000 customers, including more than half of Fortune 100 companies.
Thus, the enhancements to Atlas this week and the launch of the new MongoDB AI Applications Program. The latter, which the company calls MAAP for short, brings together not just MongoDB’s platform but also partners from companies offering foundational models, cloud infrastructure, security and AI consultancy services.
Greg Maxson, senior director of AI go-to-market and strategic partnerships, said MAAP was developed based on MongoDB’s experiences building generative AI applications with “hundreds” of early movers in the space.
“MAAP simplifies common first-mile challenges and streamlines the development process,” Maxson said.
He added the program “accelerates time to development,” with customers who have used the MAAP approach able to deploy generative AI applications in about six weeks.
MongoDB, of course, isn’t the only cloud database company out there. Gartner noted the company competes with services from the likes of AWS, Oracle, Microsoft, Aerospike, Couchbase, Cloudera, Cockroach Labs, MariaDB, Redis, and Snowflake, among others.
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