MongoDB Developer Data Platform Debuts
June 8, 2022
MongoDB
unveiled its developer data platform vision
with a series of new groundbreaking
capabilities at MongoDB’s annual conference,
MongoDB World at the Javits Center in New
York City. With these announcements, MongoDB
is empowering development teams to innovate
faster by addressing a wider set of use
cases, servicing more of the data lifecycle,
optimizing for modern architectures, and
implementing the most sophisticated levels
of data encryption, all within a single
integrated developer data platform.
“Hundreds of millions of new applications
will be developed over the coming years that
deliver compelling customer experiences,
enable new capabilities to transform
businesses, and increase operational
efficiency via more sophisticated automation
– and these applications all require a
highly scalable, cloud-native, globally
distributed data platform,” said Dev
Ittycheria, President & CEO of MongoDB. “Our
vision is to offer a developer data platform
that provides a modern and elegant developer
experience, enables broad support for a wide
variety of use cases, and delivers the
performance and scale needed to address the
most demanding requirements.”
Addressing a wider spectrum of use cases
MongoDB has extended its compelling and
unique approach of working with data beyond
operational and transactional use cases to
serve search and analytics use cases, all
within a unified platform. These
enhancements allow teams to accomplish more
while preserving a consistent developer
experience and reducing the complexity of
the data infrastructure required to support
modern applications.
MongoDB announced a number of
capabilities that make it easier for
developers to leverage in-app analytics and
power richer application experiences. Column
Store Indexes, available later this year,
will enable users to create and maintain a
purpose-built index that dramatically speeds
up many common analytical queries without
requiring any changes to the document
structure or having to move data to another
system. Furthermore, analytics nodes can now
be scaled separately, allowing teams to
independently tune the performance of their
operational and analytical queries without
over- or under-provisioning.
MongoDB time series collections make it easier, faster, and lower cost to build applications that monitor physical systems, track assets, or deal with financial data. In the upcoming MongoDB 6.0 release, time series collections will support secondary indexes on measurements, and feature read performance improvements and optimizations for sorting time-based data more quickly.
Atlas Search is the fastest and easiest way to build relevance-based search capabilities into applications. Now, with Search Facets, developers are able to rapidly build search experiences that allow end users to more seamlessly browse, narrow down or refine their results by different dimensions.
Servicing more of the data lifecycle
MongoDB
announced new products and capabilities that
enable development teams to better analyze,
transform, and move their data in Atlas
while reducing reliance on batch processes
and ETL jobs that can create delays, limit
productivity, and increase costs.
Atlas Data Lake will feature fully
managed storage capabilities that provide
the economics of cloud object storage while
optimizing for high-performing analytical
queries. Atlas Data Lake reformats, creates
partition indexes, and partitions data as it
is ingested from Atlas databases, creating a
highly performant companion data lake.
Atlas’s Data Federation capabilities allow teams to create virtual databases so that they can work with data that resides in a range of different sources. Development teams can query, transform, or create views across one or more collections, MongoDB clusters, and storage buckets.
Atlas SQL Interface provides a great experience for data analysts, who work mainly in SQL tools, to interact with Atlas data in a read-only interface. This makes it easy to natively query and visualize Atlas data with SQL-based tools while preserving the flexibility of the document model. Additionally, you can query data across Atlas clusters and cloud object stores using SQL without the need for data manipulation, schema definition, or flattening of data.
Optimizing for modern application
architectures
In addition to supporting a wide range of
workloads, organizations need to have the
flexibility to deploy the right application
architectures to serve their needs.
Atlas Serverless is now generally
available and allows users to support a wide
range of application requirements with
little to no initial configuration and
ongoing capacity management. Users benefit
from the ability to scale to zero and deploy
in all three major cloud providers, and
tiered pricing automatically reduces the
cost for large workloads without upfront
commitments.
Vercel integration will allow teams using Vercel’s platform to develop, preview and ship websites and applications to more easily get started with MongoDB Atlas as their backend database. Using Vercel's Integrations Marketplace, developers can now deploy new web experiences on Atlas with zero configuration and instantly start building with documents that map directly to their code.
Cluster-to-Cluster Synchronization provides the continuous data synchronization of MongoDB clusters across environments whether in Atlas, in private cloud, on-premises, or on the edge. Cluster-to-Cluster Synchronization allows users to easily migrate data to the cloud, create test environments, create dedicated analytics environments, and support data residency requirements.
Atlas Device Sync connects a fully managed backend database in Atlas to Realm, the popular mobile database on edge and mobile devices. MongoDB’s new Flexible Sync option grants granular control over the data synced to user applications with intuitive language-native queries and hierarchical permissions.
The Data API is a secure API for accessing Atlas data over HTTPS without any operational overhead. This provides developers a way to easily extend Atlas data into other apps and services in the cloud or into their serverless architectures.
"The ability to leverage Cluster-to-Cluster
Synchronization (C2C) for our many existing
MongoDB-based travel applications is
something we've been wanting for a long time
and will be a huge benefit to us. It will
greatly improve many facets of our software
lifecycle, such as supporting "blue/green"
deployments, data distribution, cloud
migration and further increasing our high
levels of geographic availability for our
airline customers," said Sylvain Roy, Senior
Vice-President, Technology Platforms &
Engineering (TPE), Amadeus.
Implementing the most sophisticated levels
of data encryption
Every
organization must be able to secure the most
sensitive information in any environment
without compromising the ability to build
rich application experiences that make use
of that data. While existing encryption
solutions (in motion and at rest) cover many
use cases, none of them protect sensitive
data while it is in use. Queryable
Encryption, available in preview with
MongoDB 6.0, introduces the industry’s first
encrypted search scheme using breakthrough
cryptography engineering. This technology
gives developers the ability to query
encrypted sensitive data in a simple and
intuitive way without impacting performance,
with zero cryptography experience required.
Data remains encrypted at all times on the
database, including in memory and in the
CPU; keys never leave the application and
cannot be accessed by the database server.
This end-to-end client-side encryption uses
novel encrypted index data structures in
such a way that for the first time,
developers can run expressive queries on
fully encrypted confidential workloads.
Queryable Encryption is based on well-tested
and established standard NIST cryptographic
primitives to provide strong protection from
attacks against the database, including
insider threats, highly privileged
administrators and cloud infrastructure
staff.