MongoDB Atlas Vector Search dramatically
simplifies securely building real-time generative AI applications
to create highly accurate and personalized end-user
experiences
MongoDB Atlas Search Nodes provide dedicated
infrastructure to scale generative AI and relevance-based search
workloads with up to 60 percent faster query times
AT&T Cybersecurity and Pathfinder Labs
among customers building and scaling next-generation applications
using MongoDB Atlas Vector Search and MongoDB Atlas Search
Nodes
NEW YORK,
Dec. 4,
2023 /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB)
today announced the general availability of MongoDB Atlas Vector
Search and MongoDB Atlas Search Nodes to make it faster and easier
for organizations to securely build, deploy, and scale
next-generation applications at less cost. MongoDB Atlas Vector
Search simplifies bringing generative AI and semantic search
capabilities into real-time applications for highly engaging and
customized end-user experiences using an organization's operational
data. MongoDB Atlas Search Nodes provide dedicated infrastructure
for applications that use generative AI and relevance-based search
to scale workloads independent of the database and manage
high-throughput use cases with greater flexibility, performance,
and efficiency. Together, these capabilities on MongoDB Atlas
provide organizations with the required foundation to seamlessly
build, deploy, and scale applications that take advantage of
generative AI and robust search capabilities with greater
operational efficiency and ease of use. To get started with MongoDB
Atlas, visit mongodb.com/atlas.
"Customers of all sizes from startups to large
enterprises around the world tell us they want to take advantage of
generative AI and relevance-based search to build next-generation
applications that reimagine how businesses find ways to deeply
personalize engagement with their customers, drive increased
efficiency through automation, and propel new product development.
But these customers know that complexity is the enemy of speed, and
the choice of a database is fundamental to ensuring not just the
success of an application but also how fast it can be built,
deployed, and continually updated with the flexibility and scale
needed to meet shifting end-user demands," said Sahir Azam, Chief Product Officer at MongoDB.
"With the general availability of MongoDB Atlas Vector Search and
MongoDB Atlas Search Nodes, we're making it even easier for
customers to use a unified, fully managed developer data platform
to seamlessly build, deploy, and scale modern applications and
provide end users with the types of personalized, AI-powered
experiences that save them time and keep them engaged."
As the use of MongoDB Atlas as an integrated
developer data platform has rapidly grown, and more customers want
to take advantage of generative AI, they have asked for more even
integrated capabilities to meet the shifting demands of their
businesses and end users—and MongoDB is meeting that demand:
- Integrate AI-powered capabilities into applications
with MongoDB Atlas Vector Search: Unlike an add-on
solution that only stores vector data, MongoDB Atlas Vector Search
powers generative AI applications by functioning as a highly
performant and scalable vector database with the added benefits of
being integrated with a globally distributed operational database
that can store and process all of an organization's data. This
allows developers to use a single API to more easily build
generative AI applications for virtually any type of workload
across major cloud providers without the complexity of unnecessary
data duplication and synchronization that bolt-on vector databases
require. MongoDB Atlas Vector Search allows customers to easily and
securely use retrieval-augmented generation (RAG) with pre-trained
foundation models (FMs) to leverage their own up-to-date data for
intelligent applications. As a result, applications built with
MongoDB Atlas Vector Search can provide more accurate and relevant
responses for specific domains and AI-powered use cases without the
complex and tedious work of training and fine-tuning FMs or tacking
on a separate database to store and process vector data.
With the general availability of MongoDB Atlas Vector Search,
customers can quickly build, deploy, and scale AI-powered features
from semantic search to image comparison to highly personalized
recommendations using a single, familiar, unified platform with
minimal developer friction. Because MongoDB Atlas uses a flexible
and scalable document-based data model that supports virtually any
type of data, customers can easily combine a breadth of queries for
vector data, analytical aggregations, text-based search, geospatial
data, and time series data unavailable with other solutions to
augment RAG and further refine responses to end-user requests. For
example, an end-user could request, "Find real estate listings with
houses that look like this image, were built in the last five
years, and are in an area within seven miles north of downtown
Seattle with top-rated schools and
walking distance to parks," and an application running on MongoDB
Atlas can quickly and seamlessly provide an FM the right data to
produce accurate results—without the complexity of processing
separate queries across multiple data stores that can increase
response times and degrade end-user experiences. To get started,
visit mongodb.com/products/platform/atlas-vector-search.
- Isolate and scale generative AI and search workloads on
MongoDB Atlas: Now generally available, MongoDB Atlas
Search Nodes provide dedicated infrastructure for customers to
manage generative AI and relevance-based search workloads that use
MongoDB Atlas Vector Search and MongoDB Atlas Search independent of
the core operational nodes of their database—enabling workload
isolation, cost optimization, and better performance at scale. For
example, a retailer running promotions leading up to a holiday
shopping event may want to isolate and scale workloads for
AI-powered chatbots and relevance-based search in specific
geographical regions independent of their global operational
database to optimize performance.
With MongoDB Atlas Search Nodes, customers can improve performance
by reducing query times by up to 60 percent to provide end users
optimized AI-powered and relevance-based search experiences using
their operational data with a single API, all with less complexity.
To get started, visit mongodb.com/atlas/search.
Customers across industries including AT&T
Cybersecurity, Pathfinder Labs, and many more are building and
scaling next-generation applications with MongoDB Atlas Vector
Search and MongoDB Atlas Search Nodes.
AT&T Cybersecurity simplifies securing
valuable business assets by providing broad cybersecurity
experience and award-winning services for network security,
extended detection and response, and endpoints. "AT&T
AlienVault is the world's most trusted and widely used open source
Security Information and Event Management (SIEM) platform, and the
ability to find relevant information with low latency is critical
in the world of cybersecurity, threat detection, and incident
response management. A delay could mean the difference between a
successful detection and response, or a breach causing unfathomable
destruction," said Matthew Schneid,
Chief Architect at AT&T Cybersecurity. "We are very excited to
continue our usage of Atlas Search Nodes as it becomes generally
available. It has helped us host larger search deployments and
scale our workloads, while significantly boosting the performance
of complex search queries. Further, the platform as a whole, and
the approach MongoDB has taken to build the feature in a way that
engineers enjoy working with it regularly, is a huge plus."
Pathfinder Labs is a global leader in software
development specializing in protecting vulnerable children by
empowering law enforcement agencies with state-of-the-art
technology. "We are committed to delivering investigators the most
advanced tools, and we cannot accept delays in removing a child
from harm due to investigations being overwhelmed by large amounts
of disparate data. In situations where every minute impacts a
child's well-being, these tools must enable investigators to
swiftly navigate data challenges and rapidly apprehend
perpetrators," said Bree Atkinson,
CEO of Pathfinder Labs. "By using MongoDB Atlas, we're able to make
data-driven decisions swiftly, boosting our productivity and
decision-making speed. And with MongoDB Atlas Vector Search, we
don't have to incorporate multiple tools to achieve AI-powered
semantic search functionality. Now, we can handle it all from a
single platform that delivers the scale and performance we require
with less complexity and operational overhead."
MongoDB Atlas Vector Search is generally
available today on AWS, Google Cloud, and Microsoft Azure. MongoDB
Atlas Search Nodes are generally available today on AWS, with
availability on Google Cloud and Microsoft Azure coming soon.
About MongoDB Atlas
MongoDB Atlas is
the leading multi-cloud developer data platform that accelerates
and simplifies building modern applications with a highly flexible,
performant, and globally distributed operational database at its
core. By providing an integrated set of data and application
services in a unified environment, MongoDB Atlas enables
development teams to quickly build with the security, performance,
and scale modern applications require. Millions of developers and
tens of thousands of customers across industries—including Cathay
Pacific, Cisco, GE Healthcare, Intuit, Toyota Financial Services,
and Verizon—rely on MongoDB Atlas every day to innovate more
quickly, efficiently, and cost-effectively for virtually every use
case across the enterprise. To get started with MongoDB Atlas,
visit mongodb.com/atlas.
About MongoDB
Headquartered in
New York, MongoDB's mission is to
empower innovators to create, transform, and disrupt industries by
unleashing the power of software and data. Built by developers, for
developers, MongoDB's developer data platform is a database with an
integrated set of related services that allow development teams to
address the growing requirements for today's wide variety of modern
applications, all in a unified and consistent user experience.
MongoDB has tens of thousands of customers in over 100 countries.
The MongoDB database platform has been downloaded hundreds of
millions of times since 2007, and there have been millions of
builders trained through MongoDB University courses. To learn more,
visit mongodb.com.
Forward-looking Statements
This press
release includes certain "forward-looking statements" within the
meaning of Section 27A of the Securities Act of 1933, as amended,
or the Securities Act, and Section 21E of the Securities Exchange
Act of 1934, as amended, including statements concerning
enhancements of MongoDB's technology and offerings. These
forward-looking statements include, but are not limited to, plans,
objectives, expectations and intentions and other statements
contained in this press release that are not historical facts and
statements identified by words such as "anticipate," "believe,"
"continue," "could," "estimate," "expect," "intend," "may," "plan,"
"project," "will," "would" or the negative or plural of these words
or similar expressions or variations. These forward-looking
statements reflect our current views about our plans, intentions,
expectations, strategies and prospects, which are based on the
information currently available to us and on assumptions we have
made. Although we believe that our plans, intentions, expectations,
strategies and prospects as reflected in or suggested by those
forward-looking statements are reasonable, we can give no assurance
that the plans, intentions, expectations or strategies will be
attained or achieved. Furthermore, actual results may differ
materially from those described in the forward-looking statements
and are subject to a variety of assumptions, uncertainties, risks
and factors that are beyond our control including, without
limitation: the impact the COVID-19 pandemic may have on our
business and on our customers and our potential customers; the
effects of the ongoing military conflict between Russia and Ukraine on our business and future operating
results; economic downturns and/or the effects of rising interest
rates, inflation and volatility in the global economy and financial
markets on our business and future operating results; our potential
failure to meet publicly announced guidance or other expectations
about our business and future operating results; our limited
operating history; our history of losses; failure of our platform
to satisfy customer demands; the effects of increased competition;
our investments in new products and our ability to introduce new
features, services or enhancements; our ability to effectively
expand our sales and marketing organization; our ability to
continue to build and maintain credibility with the developer
community; our ability to add new customers or increase sales to
our existing customers; our ability to maintain, protect, enforce
and enhance our intellectual property; the growth and expansion of
the market for database products and our ability to penetrate that
market; our ability to integrate acquired businesses and
technologies successfully or achieve the expected benefits of such
acquisitions; our ability to maintain the security of our software
and adequately address privacy concerns; our ability to manage our
growth effectively and successfully recruit and retain additional
highly-qualified personnel; and the price volatility of our common
stock. These and other risks and uncertainties are more fully
described in our filings with the Securities and Exchange
Commission ("SEC"), including under the caption "Risk Factors" in
our Quarterly Report on Form 10-Q for the quarter ended
July 31, 2023, filed with the SEC on
September 1, 2023 and other filings
and reports that we may file from time to time with the SEC. Except
as required by law, we undertake no duty or obligation to update
any forward-looking statements contained in this release as a
result of new information, future events, changes in expectations
or otherwise.
MongoDB Public
Relations
press@mongodb.com
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SOURCE MongoDB, Inc.