MapR Redefines Big Data Landscape with Dedicated Enterprise-Grade Spark Distribution

Integrates real-time data platform with complete Spark stack

Chennai: MapR Technologies, Inc., provider of the industry’s only converged data platform, announced today at Spark Summit a new enterprise-grade Apache Spark Distribution. This new distribution includes the complete Spark stack engineered to support advanced analytic applications, along with patented innovations in the MapR Platform, plus key open source projects that complement Spark. This new and unique Spark-based offering redefines how companies leverage their big data. From the deployment of real-time applications to the evolution of how those applications expand within an organization, the Spark Distribution for MapR can serve as a starting point to leverage the power of Spark as an essential component in a modern data architecture.

“ESG research shows Apache Spark adoption is poised to grow quickly, with 16% of businesses already in production and another 47% very interested in implementing Spark,” said Nik Rouda, senior analyst, ESG. “As such, Spark will power the next wave of big data. Yet enterprises will demand a robust platform to meet their operational requirements. MapR is helping to accelerate Spark by addressing this need.”

The new Spark Distribution option for the MapR Converged Data Platform enables all advanced analytics including batch processing, machine learning, procedural SQL, and graph computation. Because Spark runs seamlessly on MapR it benefits from the platform’s patented enterprise-grade features such as web-scale storage, high availability, mirroring, snapshots, NFS, integrated security, global namespace, etc. This native integration makes it the only reliable and production-ready platform for Spark workloads on-premise and in the cloud. Product extensions of the Spark Distribution could include real-time streaming and operational analytic capabilities, with MapR-Streams, MapR-DB, and Hadoop as add-ons.

“This is a great example of MapR continued commitment to open source Apache Spark," said John Tripier, senior director of business development, Databricks. "MapR was early to recognize the impact Spark would have on the big data landscape, and we are excited to see them extending the power of Spark for their enterprise customers with this announcement."

With a distribution now optimized for Spark, MapR expands its commitment to the open source community with offerings tailored toward specific compute processing engines. The new distribution includes the latest Spark version delivering in-memory processing for big data, enabling faster application development and allowing for code reuse across batch, interactive, and streaming applications. MapR will also leverage its Spark Distribution in its Quick Start Solution offerings, which include pre-built templates, configuration and installation. The most popular use cases for Spark include building data pipelines and developing advanced analytical applications leveraging machine learning.

“We’ve built this new distribution to make it easier for customers that leverage the power of Spark for their big data initiatives,” said Anoop Dawar, vice president product management, MapR Technologies. “We’ve seen significant growth of customers deploying Spark as their primary compute engine. We believe this gives our customers a converged compute and storage engine for batch, analytics, and real-time processing that helps build and deploy applications rapidly.”

Availability

The new Spark Distribution is available now in the MapR Converged Community Edition and the MapR Converged Enterprise Edition.

Resources

Visit MapR this week at Spark Summit where the company will be showcasing its product offerings, free online Spark courses, and Spark Certification.

Read about additional Spark Distribution details on the MapR Converge Community page here.

Learn what technology partners have to say about the Spark Distribution from MapR here.