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MongoDB Enables Consolidation Around Its NoSQL Database Platform with 3.4 Release


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MongoDB has introduced a new release of its NoSQL document database platform with key features that support additional data models, the combination of operational and analytical processing, elastic cross-region scaling, and tooling to simplify data management for customers.

According to the company, this release places MongoDB at the center of digital transformation initiatives for enterprises all over the world, combining always-on transactions with real-time analytics.

Over the last 10 years, many new products, services, and ways to solve data problems have emerged, but the truth is that “nobody really wants to run 20 different database management systems in their enterprise,” said Eliot Horowitz, CTO and cofounder of MongoDB, noting that what the company is seeing now is a desire for consolidation. With this release, he said, features and capabilities have been added to support MongoDB being the platform that organizations coalesce around.

Supporting Analytics With "MultiModel" Capabilities

With MongoDB 3.4, the company is introducing native graph analytics and faceted navigation to address 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, the company says. While there are many graph databases, when the need for graph technology comes up, users don’t want to use a separate graph database and so it makes sense for MongoDB to have that capability, said Horowitz. The same is true for faceted search, he added, noting that this is something that in the past people had to do with a discrete product but now they will be able to do it inside of MongoDB effectively. At the end of the day, Horowitz said, it is about simplifying the architecture so “developers can focus on adding features instead of synchronizing products.”

Additionally, a new SQL interface is available that, the company says, improves performance, simplifies setup, and adds support for Windows, while enabling business analysts, data scientists, and executives to use traditional BI tools. This BI connector allows business users and others who work with tools such as Tableau and Qlik to take their standard tools and point it at the data sitting in MongoDB to answer their questions without having to take the data out and store it in something else, Horowitz observed.

With this release, the MongoDB Connector for Apache Spark has also been updated to support the latest Spark 2.0 release.

Multi-Data Center Deployments Reduces Latency, Increases HA, and Supports Governance Objectives

To further support the needs of global operations, in this release, MongoDB 3.4 also introduces capabilities that simplify deployments and increase flexibility.

With Zones, MongoDB offers an elastic database partitioning capability designed for multi-region deployments. Zones allow DBAs 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 with an interface to the feature. This capability addresses increasing concerns with data being more redundant because users are less tolerant today of downtime, and also less tolerant of latency, said Horowitz. In keeping with those requirements, the Zones capability is focused on keeping data close to people and supporting global data governance needs about where data can be stored geographically, he noted.

Also, supporting HA, faster elastic operations reduce the time associated with balancing data across distributed clusters to address administrators’ need to scale their deployments up and down quickly and with no application downtime.

To support DBAs who want to work with MongoDB but are not yet expert with the technology, Horowitz said that MongoDB Compass, which came out last year, is focused on making it easier to work with the NoSQL database using a GUI tool that now has more functionality. MongoDB Compass is designed to allow users to easily analyze and understand the contents of their data collections within MongoDB and perform queries, without requiring knowledge of MongoDB query syntax.

Supporting private cloud deployments for database as a service, MongoDB Ops Manager introduces Server Pools and native Cloud Foundry integration, to help provision and manage database resources within cloud-native infrastructure.

And, furthering the goal of making MongoDB easier to use within enterprises for more users, the release also offers read-only views that simplify data access for application development teams, and provide fine-grained control of sensitive data, such as PII. With the filtering and masking of data, views permit organizations to more easily meet compliance standards in regulated industries by reducing the risk of data exposure.

MongoDB Atlas

Finally, using MongoDB Atlas, an elastic, on-demand cloud database as a service launched in summer 2016, organizations can spin up and evaluate the new features in MongoDB 3.4. In addition, support for AWS VPC peering is being added to MongoDB Atlas, 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 in a fast and secure way without using public IP addresses that could compromise data security.

MongoDB 3.4 will be generally available in early December.

For more information, download the “What’s New in MongoDB 3.4” white paper.


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