GridGain Updates its Two Open Source-based Big Data Computing Platform with DevOps for Greater Insights

By CIOReview | Tuesday, June 30, 2015
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SAN FRANSCICSO, CA: GridGain, innovator behind open source and commercial in-memory data fabric solutions, announces two new releases that integrates with Spark deployments, Apache Mesos and Apache YARN-based datacenters and Apache Zeppelin Projects which is currently in incubation under the Apache Software Foundation.

The two in-memory data fabric powered by Apache Ignite (also incubating under the Apache Software Foundation) are GridGain Enterprise edition v7.1 and GridGain Community edition v1.1. They include new DevOps management and automation features that assist Ignite clusters blend into Spark clusters, Mesos- or YARN-based datacenter environments. They also enable data scientists to queue in-memory clusters using SQL and visualize results in Apache Zeppelin (incubating).

The GridGain In-Memory Data Fabric Enterprise Edition offers ultra-low latency at any scale, horizontal and vertical scaling, configurable data consistency and enhanced security. The new version 7.1 features spark shared memory that supports ANSI-99 compliant SQL queries over the shared data and allows users to share state in-memory between isolated Spark jobs using native Spark RRD and DataFrame APIs.

Integration with Apache Mesos and YARN enables users to install and configure Ignite resources across servers, scale Ignite resources based on demand and automatically manage Ignite resources within their data centers. Integration with Apache Zeppelin (incubating) enables data scientists to utilize Ignite SQL and Ignite APIs to provide interactive SQL capabilities and graph-visualize SQL queries.

GridGain Community edition v1.1 also comprises the above features and includes optional LGPL dependencies and additional testing by GridGain.

“The explosive growth of data consumption and the rapidly falling costs of DRAM have been aggressive drivers for new data access and processing techniques handling Big Data, and more specifically Fast Data, at the speed of RAM,” said Abe Kleinfeld, President and CEO, GridGain. “These new GridGain releases directly address needs our customers have asked for: The ability to easily share state between otherwise isolated Spark jobs and seamlessly blend their Ignite, Spark and Hadoop clusters within a Mesos- or YARN-based datacenter environment.”