Hadoop Compatibility Allows GridGain to Accelerate Hadoop and Apache Spark

The GridGain® in-memory computing platform, built on Apache® Ignite, posesses seamless Hadoop compatibility. The GridGain Hadoop Accelerator means the GridGain in-memory computing platform can accelerate Hadoop and reduce MapReduce and HIVE jobs by 10 times in ten minutes.

GridGain Integrates with Apache Spark and Hadoop

If you are using Apache Spark with Hadoop, GridGain is a powerful complement to Spark. When used with GridGain, Spark queries can run much faster because GridGain indexes the Spark RDDs so Spark queries do not require a full scan of the data. GridGain also makes the Spark RDDs mutable so you can share state between Spark applications and jobs.

The GridGain Data Lake Accelerator and Hadoop

The GridGain Data Lake Accelerator, built on the GridGain in-memory computing platform, accelerates data lake analytics and access by providing bi-directional integration with Hadoop. This integration brings the historical data into the same in-memory computing layer as the real-time operational data, enabling real-time analytics and computing on the combined data.

Development Package
GridGain and Hortonworks

In addition, GridGain is a certified member of the Hortonworks Partnerworks ISV/IHV program. This means that all GridGain in-memory computing products are guaranteed to work with the Hortonworks Connected Data Platforms.