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MapR Seeks Advantage From Cloudera-Hortonworks Merger With New Software Release, Data Assessment Service

Saying the complex merger of its rivals will create customer uncertainty, MapR Technologies has launched the "Clarity Program" to provide a free data assessment service to woo Cloudera and Hortonworks users to its data management platform.

With rivals Cloudera and Hortonworks working through a complex and possibly lengthy merger, MapR Technologies is offering potential converts a new release of its big data platform and a free assessment of an organization's data environment and needs.

MapR says its new Clarity Program, which includes the updated MapR Data Platform and the free StepUp assessment, is designed to provide customers with a comprehensive understanding of their current data environment and the best practices to support artificial intelligence, cloud, containers and Internet of Things deployments.

The software and services are designed to entice Cloudera and Hortonworks customers that may be feeling uncertainty following the recent announcement that the two big data software vendors will merge under the Cloudera name.

[Related: Map R Launches The Next Generation Of Its Big Data Platform For Analytics And AI]

"We're kind of skeptical that they'll get that done in a year," said Bill Peterson, vice president of industry solutions at MapR, referring to the Cloudera-Hortonworks merger and their need to combine and integrate their product lines and phase out overlapping products. "There's a lot of things to work through and rationalize here."

"And what kind of innovation can occur at the same time?" he said in an interview with CRN. "Innovation kind of goes on the shelf until they get that done."

The free StepUp data assessment service is targeted squarely at identifying prospects among current Cloudera and Hortonworks users, Peterson said.

The service taps into MapR's professional services to assess an organization's data architecture, workflows, applications and use cases. The service covers performance planning and recommendations, feature mapping to identify gaps and needs, and step-by-step implementation plans for on-premise, cloud and edge system execution, according to the company.

The Clarity data assessment is designed to be a one-week engagement, although MapR said the length of an assessment can hinge on the complexity of the data management environment.

MapR works with a number of systems integrators and consultants, including Deloitte and The Hackett Group, and Peterson said partners could be called in to help provide the assessment services.

The updated release of the MapR Data Platform offers a number of new capabilities and features covering AI, cloud, container and Internet of Things technologies.

The software offers a common data management, security and protection model for uniform data governance – data security and management are not based on data type or access method, according to the company. Those capabilities extend to edge systems for IoT applications. And the product supports Kafka KSQL for working with streaming data applications.

"We view data governance as an enterprise-wide challenge," Peterson said.

Supporting stateful applications in containers can be a challenge, according to MapR. One of the advances in the new edition is support for frictionless data access for containerized stateful applications. (Stateful applications save client data generated by activities from one session to the next.

The new Clarity edition also supports direct data access with native Kubernetes volume drivers and the ability to use containers and Kubernetes directly with Nvidia containers.

The new software offers new S3-compatible APIs that provide cross-cloud data synchronization and replication, coordinating data access and flows across Hadoop installations, and allowing on-premises, file-based applications to directly access object storage across cloud systems.

And the new software provides broad support for diverse data management and logistics capabilities with standard interfaces to such tools as TensorFlow, Caffe and PyTorch, as well as to NVIDIA's RAPIDS open-source software.

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