While MapReduce still enjoys widespread use in the Hadoop ecosystem, the number of new deployments that are being brought online is declining. And the trend has not gone unnoticed by the vendors that make their living selling commercial versions of the software. At MapR Technologies Inc., the leadership team is already refocusing its growth plans on Spark.

The company today unveiled a commercial distribution of the speedy MapReduce alternative that promises to lower the entry barrier for organizations looking to modernize their analytics environments. The offering includes the project’s core data crunching component and all the extensions available from the upstream project, which support a broad range of use cases. Customers can leverage Spark to perform stream processing, map out the relationships among disparate records and even run machine running algorithms. Rounding out the lineup is a SQL component that provides the ability to interact with the framework using structured query syntax.

The latter feature can be tremendously handy for traditional enterprises that may not have a lot of experience with modern data crunching frameworks, but employ analysts who are already well-versed in SQL. Such companies usually also have a long list of reliability requirements that MapR’s Spark distribution attempts to address by borrowing key functionality from its Hadoop flavor. The offering provides high-availability, replication features and an integrated security control mechanism to prevent information access, among other capabilities.

MapR debuted its Spark flavor within hours of Microsoft Corp. making the engine available on its cloud-based HDInsight data processing service. And with other major players like Cloudera Inc. also embracing the framework, the future of MapReduce isn’t looking particularly bright. In the big picture, however, the analytics ecosystem only stands to benefit from adopting newer and better technologies.

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