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Technology Vendors Embrace MapR 5.0 Platform

Including Centrify, Dataguise, Datameer, HP Security Voltage, Informatica, Protegrity, Syncsort, Talend, Teradata, Waterline Data, Zaloni

MapR Technologies, Inc. announced that technology vendors have embraced version 5.0 of MapR Distribution including Hadoop to extend the value of their offerings with real-time Hadoop, security and self-service data exploration and agility.

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MapR extends its lead in production Hadoop with more innovations in security and data governance in MapR 5.0. With the new Apache Drill Views feature, organizations have field-level access controls on unstructured data files. In addition, analysts gain agile data governance by sharing data sets with custom access permissions via Views and eliminating the need to involve IT intervention for access control. Also, the comprehensive auditing capabilities in MapR 5.0 let organizations log user activity, which is particularly important for understanding user behavior as well as for achieving regulatory compliance. These security and data governance advancements lay the foundation for value-adding partner technologies.

With a growing big data partnership ecosystem, MapR enhances the protection and management of sensitive Hadoop data to joint customers. MapR partners, including Centrify, Dataguise, Datameer, HP Security Voltage, Informatica, Protegrity, Syncsort, Talend, Teradata, Waterline Data and Zaloni, have embraced the MapR Distribution version 5.0 to implement production-ready big data solutions.

MapR 5.0 builds upon the ente,ise-proven security capabilities in earlier versions of our production-grade Hadoop distribution,” said Anil Gadre, SVP, product management, MapR. “We now address customer requirements around field-level access control on unstructured data and comprehensive auditing capabilities. These add on to our existing security capabilities, which include our extensible authentication framework, fine-grained access controls and features like volumes and snapshots that support auditing and lineage.

As a lader in enterprise secure identity solutions, we see the rapidly maturing demand for stringent security capabilities in Hadoop,” said Shreyas Sadalgi, SVP, business development, Centrify Corporation. “The new capabilities in MapR 5.0 for field-level access controls with comprehensive auditing demonstrate MapR ongoing commitment to enabling secure Hadoop deployments. Centrify’s capabilities around privileged identity management extends MapR enhancements for increased user productivity and enhanced security. Centrify helps MapR customers rapidly deploy Hadoop in Secure Mode with simplified Active Directory-based authentication for both Hadoop administrators and end users. We are pleased to work with MapR on meeting the security requirements of today’s enterprise-grade production Hadoop deployments.

These new data-centric features from MapR couldn’t be more timely, as enterprises are leveraging Hadoop beyond batch analytics and driving new applications that drive up the consumption of personal and private data in Hadoop, but must do so in a protected and audit-able way. In particular, MapR expanded security for authorization and auditing capabilities in 5.0, fits perfectly with Dataguise support for sensitive data discovery, encryption, masking, and monitoring,” said Jeremy Stieglitz, VP, products, Dataguise, Inc. “We are pleased to fuse these data-centric components together with MapR to deliver a new generation of secure Hadoop deployments.

Datameer is very excited about MapR security and data governance announcements, as they align extremely well with our own governance capabilities, announced just last week. The MapR 5.0 innovations for field-level access control and auditing are great complements to our secure data views and auditing capabilities,” said Andrew J. Brust, senior director, technical product marketing and evangelism, Datameer, Inc. “With our other governance features, including data lineage, impact analysis and data profiling, along with our Native Hadoop architecture, the Datameer and MapR combination has never been stronger.

A key requirement in today’s secure Hadoop environments is obfuscating sensitive data elements through data-centric techniques such as HP Format Preserving Encryption and HP Secure Stateless Tokenization,” said Reiner Kappenberger, global product management, HP Security Voltage. “Our technologies combined with the flexible access controls and auditing capabilities in MapR 5.0 help to reduce the cost of securing data in Hadoop, meet regulatory compliance, and protect sensitive data at rest, in motion, and in use.

As enterprises go beyond pilot Hadoop deployments and into production, they will face challenges with data quality, data governance and data security, specifically the proliferation of private and sensitive information,” said Ash Parikh, VP, product marketing, data integration and security, Informatica Corporation. “Informatica, together with MapR, which delivers an innovative platform for production Hadoop, helps customers operationalize big data projects intelligently and repeatably by delivering trusted big data for more accurate and confident big data analytics.

When field-level access controls made possible by the new Drill Views feature in MapR 5.0 are combined with the advanced strong encryption and tokenization technologies offered by the Protegrity big data Protector, organizations can deploy a dat,ic security solution that protects unstructured data in Hadoop environments from a variety of attack vectors and with different levels of granularity,” said Suni Munshani, CEO, Protegrity Corporation. “Together, MapR and Protegrity are helping clients implement the highest levels of data security and compliance across the enterprise while maintaining data usability for business processes and analytics.

Modernizing legacy infrastructures to leverage Hadoop requires a critical data governance step: data integration. As a lon saning leader in the data integratin sace we often help customers deliver sensitive data to Hadoop. The Drill Views feature in the MapR Distribution is a great technology for our joint customers to limit access to sensitive data only to authorized users,” said Tendu Yogurtcu, GM, big data business unit, Syncsort, Inc.

The many features in the MapR Distribution that support security and data governance demonstrate the technology leadership by MapR as a provider of Hadoop. The new platform-wide auditing feature in MapR 5.0 is especially a good complement to the powerful data integration, profiling, and data quality capabilities that Talend provides,” said Ashley Stirrup, CMO, Talend, Inc. “We are excited to partner with MapR to deliver a powerful joint solution for getting the most value out of big data.

Agility should be a key requirement in any big data governance strategy,” said Chris Twogood, VP, product and services marketing, Teradata Corp. “Teradata Loom avoids an IT bottleneck by providing Hadoop end users agile mechanisms to find, understand, prepare, secure, and manage data throughout its lifecycle. We see a similar opportunity for agility in the authorization features in ‘Drill Views,’ which empower analysts to quickly share specific elements of their data sets with other analysts.

The need to reign in large amounts of data is ever increasing. The latest version of Apache Drill in MapR 5.0 provides a compelling and unique way to provision big data access controls while promoting agility. Waterline Data is excited to work with MapR to provide joint customers with a comprehensive big data governance solution that finds, understands, governs, provisions, and protects big data,” said Oliver Claude, CMO, Waterline Data.

MapR has long had unique features like volumes and consistent snapshots to support various data governance disciplines,” said Ben Sharma, CEO, Zaloni, Inc. “The 5.0 release builds on that foundation with auditing and granular, field-level access controls. We are pleased to work with MapR to deliver business-critical use cases based on the data lake model, leveraging Zaloni Bedrock as the comprehensive platform for Hadoop data lake management that complements MapR core capabilities.

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