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MapR Powers DataOps for Companies to Unleash Greater Value from All Data

MapR Converged Data Platform 6.0 adds innovations for security, database, and automated administration across all clouds.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

MapR Technologies has released the MapR Converged Data Platform 6.0 with new advancements to help organizations achieve greater value from all of their data through DataOps teams. The major system update includes innovations that automate platform health and security and a groundbreaking database for next-generation applications. With MapR, companies benefit from a powerful modern data fabric, where volumes of data are ingested once and accessible as a single source from on-premises data centers, across clouds, and to the remote edge.

DataOps is an emerging practice utilized by large organizations with teams of data scientists, developers, and other data-focused roles that train machine learning models and deploy them to production. The goal of using a DataOps methodology is to create an agile, self-service workflow that fosters collaboration and boosts creativity while respecting data governance policies. A DataOps practice supports cross-functional collaboration and fast time to value. It is characterized by processes as well as the use of enabling technologies such as the MapR Platform.  

New benefits from the added features and updates to Version 6.0 include:

Automatic Platform Health and Security

New MapR Control System administers all data (volumes, tables, and streams) and monitors cluster health with metric co-relation in a single interface. It also includes extensible dashboards for volume metrics, including capacity, throughput, latency, and IOPs. MapR monitoring metrics are now automatically pushed to MapR Event Streams to enable easy integration with enterprise systems.

Recently announced database indexing in MapR-DB delivers auto-propagation, auto-scale, and auto-management.

Real-time Data Integration

The MapR Change Data Capture now integrates MapR-DB with MapR-ES out of the box. MapR-ES is a global event streaming system that enables real-time data ingestion and continuous stream processing. MapR-DB, in conjunction with MapR-ES, enables simplified data integration and allows multiple applications, including advanced machine learning models and deployments, to share information and be synchronized in real-time.

Secure, Discoverable Data

Users across business lines should be able to quickly find the data they need or data that could be useful to them in their analysis, but only if they have appropriate rights to that data. Version 6.0 offers new single-click security enhancements such as enforcement of authentication and more comprehensive encryption on the wire, while taking much of the guesswork out of configuring security. MapR is simpler to secure out-of-box, helping to lower the probability of a security breach.

Self-Service Data Science, Artificial Intelligence

Data analysis is increasingly being driven by machine learning/artificial intelligence to gain quick, accurate, and actionable insights, and data scientists are a driving force behind the DataOps movement. MapR makes its recently announced Data Science Refinery available for complete, self-service access to all data from within the same cluster.

Updated MapR Expansion Pack (MEP)

MEP 4.0 includes a new MapR Container for Developers, a single-node MapR deployment intended for developers that want to create new applications and services or simply learn more about MapR, support for the new Apache Myriad 0.2 release with security improvements and the ability to handle Mesos GPU bids, and enhanced support for Hive on MapR-DB JSON tables. More details on MEP 4.0 can be found here.

Other new features shipping in this release include:

  • MapR-DB database for global data-intensive applications with rich open JSON application interface (OJAI) 2.0 APIs, native secondary indexes, deep integration and optimization of Apache Drill for SQL analytics and business intelligence, and advanced analytics using native Apache Spark and Apache Hive.
  • MapR Orbit Cloud Suite enhancements offering cloud-scale multitenancy, MapR OpenStack Manila plug-in for tenant self-service provisioning of files, and edge to cloud file migrate for real-time, automatic movement of files from edge to cloud (S3).

MapR Converged Data Platform 6.0 is available now. Cloud provider marketplaces, such as Microsoft Azure, Amazon Web Services, and Oracle Cloud, will have version 6.0 available before the end of the year.

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