MongoDB, the database for giant ideas, announced MongoDB 3.4, the latest version of the popular modern database. MongoDB 3.4 adds key features that embrace additional data models, combining operational and analytical processing, elastic cross-region scaling and sophisticated operational tooling to simplify data management for customers.
The latest version is a major advance that places MongoDB at the center of enterprises’ digital transformation initiatives. Organizations today are focused on delivering new classes of applications, like the Internet of Things (IoT) and Artificial Intelligence, which have deep operational and analytical requirements. By further strengthening the product’s always-on operational and real-time analytics capabilities, MongoDB makes it easier for enterprises to consolidate their technology footprint and accelerate their digital transformation with a single database.
Leaders of nearly every business are under enormous pressure to disrupt, or be disrupted, by the advent of the digital enterprise. Organizations that know how to leverage next-generation software and data technologies to transform their businesses have an intrinsic competitive advantage,” said Dev Ittycheria, president and CEO, MongoDB. “This new release redefines what it means to be the state-of-the-art database technology, and enables innovators to build and run more mission-critical workloads on MongoDB.”
Multi-Model Functionality Powers Deeper Analytics
MongoDB 3.4 introduces native graph analytics and faceted navigation, powerful paradigms for an increasingly popular range of use cases such as e-commerce, social graph analysis and cybersecurity. Because these features are native to the database, they are fully integrated with MongoDB’s existing security, management, availability and disaster recovery features. Organizations can now deliver more powerful data access to their users, with a more simplified and secure deployment.
Developers want to access and store their data in the simplest way possible,” said Eliot Horowitz, CTO and co-founder at MongoDB. “We are continuing to add new capabilities to our query language – like graph and faceted search operators – so developers can use MongoDB for applications that previously required multiple technologies, thereby consolidating their technology footprint.”
Additionally, an all-new SQL interface is available that dramatically improves performance, simplifies setup and adds support for Windows. Industry-standard SQL empowers business analysts, data scientists and executives to quickly explore and gain new insights from modern applications using traditional BI tools installed across the enterprise. The MongoDB Connector for Apache Spark has also been updated to support the latest Spark 2.0 release, enabling data engineers to apply the latest innovations to sophisticated analytics pipelines.
Multi-Datacenter Deployments Made Simple
To meet the demands of global operations, organizations deploy applications across multiple data centers to ensure a seamless experience and “always on” availability. MongoDB 3.4 introduces a number of capabilities that simplify these deployments and increase flexibility:
- Zones, the industry’s first fully elastic database partitioning capability designed for multi-region deployments. Zones allow database administrators to associate partitions of data to specific hardware resources and locations, such as tiered storage to optimize costs or local data centers to meet data sovereignty mandates. Zones are fully integrated in MongoDB’s management tools, providing administrators a simple, intuitive interface to this powerful feature.
- Faster elastic operations dramatically reduce the time associated with balancing data across distributed clusters, giving administrators the ability to quickly scale their deployments up and down with no application downtime.
Advanced Tooling and Security for DBAs and Ops
MongoDB 3.4 also adds more of the advanced tooling and security expected by DBAs and Operations teams:
- Compass, the GUI for MongoDB that makes it easy to explore and manipulate your data, is an incredibly powerful tool. It now includes full CRUD capabilities to edit documents, the ability to intuitively create and apply document validation rules, a visual explain plans to explore query performance and real-time index usage statistics to help optimize performance.
- Simplified private cloud deployments for database as a service. MongoDB Ops Manager introduces Server Pools and native Cloud Foundry integration, making it easy to provision and manage database resources within cloud-native infrastructure.
- Read-only views simplify data access for application development teams, as well as provide fine-grained control of sensitive data, such as Personally Identifiable Information (PII). With the filtering and masking of data, Views allow organizations to more easily meet compliance standards in regulated industries by reducing the risk of data exposure.
At Baidu we have a massive and complex MongoDB deployment, with several petabytes of data and nearly 1,000 nodes. To give our users the best possible experience it’s absolutely vital that every part of that system is fast and efficient,” said Beibei Xiao, DevOps engineer at Baidu. “It’s exciting to see what’s coming in MongoDB 3.4. With MongoDB Zones we’re going to be able to have fine-grained control over exactly where the data resides to keep it as close as possible to the users who need it most. Our testing has already confirmed that parallel migrations will simplify operations in our large deployment, and will give us much faster data migration to new shards. Super high performance and elastic scaling across a massive data set make MongoDB 3.4 an even better fit for our mission-critical applications.”
Deploy 3.4 On Demand with MongoDB Atlas
Using MongoDB Atlas, an elastic, on-demand cloud database as a service, organizations can quickly spin up and evaluate the new features in MongoDB 3.4. In addition, support for AWS VPC peering is being added, enabling users to create an extended, private network that connects their application servers and services such as AWS Elastic Beanstalk and AWS Lambda to their MongoDB Atlas databases without using public IP addresses that could compromise security.
Since launching this summer, MongoDB Atlas is currently in use across hundreds of startups and industry leaders alike, including Thermo Fisher Scientific and eHarmony.
MongoDB 3.4 will be generally available in early December.
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