MapR and Typesafe put Apache's Spark to work on big data
Hadoop and dev duo deliver cluster wrapping
Big data and developer advocates are joining IBM promoting Apache’s cluster computing framework as a safe and consumable platform for business.
MapR is bowling out Spark offerings tailored to three scenarios with its implementation of the Hadoop batch-crunching framework.
MapR has announced the Real-time Security Log Analytics, Time Series Analytics and Genome Sequencing Quick-Start Solutions.
The underlying theme is that by integrating MapR with Spark you get flexible, real-time analysis and monitoring in these various fields.
MapR reckoned the integrated packages would help speed deployments of its Hadoop.
Like Spark, Hadoop is an Apache project. MapR’s Hadoop distribution integrates additional components such as Solr and Drill with features in management, security and governance that lets it charge as enterprise-class services.
Also lending its weight is Typesafe, the company founded in 2011 that lets you build reactive apps – orientated around data flows – for the Java Virtual Machine.
Typesafe will provide subscription-based support for a distribution of Spark that it’s been working on, with Mesosphere running on the Mesosphere Datacenter Operating System (DCOS).
Benjamin Hindman, founder of Mesos and the company Mesosphere, reckoned integration would reduce operational complexity and consumption of resources.
The news came after IBM put its blue weight behind Spark, announcing plans to commit engineers and training resources to Spark projects and make Spark the basis of its analytics and commerce platforms. ®
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