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MapR Technologies Inc announced the release of a new version of their Converged Data Platform. The new MapR Platform 6.0 is focused on DataOps to increase the value of data by bringing together functions from across an enterprise.

DataOps is an approach to improve quality and reduce life cycle time of data analytics for Big data applications.

MapR Platform 6.0, offers the entire DataOps team (data scientists, data engineers, systems administrators, and cluster operators) in an organization, a unified management solution.

Some top releases and features of the platform include:

  • The MapR Control System (MCS), a new centralized control system that converges all data sources and types from multiple backends. It is built on the Spyglass Initiative and provides a unified management solution for the data stored in the MapR platform. This includes files, JSON-tables, and streaming data.

MapR 6.0 MCS also comes in with:

  • A quick glance cluster dashboard
  • Resource utilization by node and by service
  • Capacity planning using storage utilization trends and per-tenant usage
  • Easy to set up replication, snapshots, and mirrors
  • The ability to manage cluster events with related metrics and expert recommendations
  • Direct access to default metrics and pre-filtered logs
  • The power to manage MapR Streams and configure replicas
  • Access to MapR DB tables, indexes, and change logs
  • Intuitive mechanisms to set up volume, table, and stream ACEs for access control
  • MapR Monitoring uses MapR Streams in the core architecture to build a customizable, scalable, and extensible monitoring framework.
  • The MapR platform also includes the latest release of MapR-DB 6.0It is a multi-model database built for data-intensive applications such as real-time streaming, operational workloads, and analytical applications.
  • The MapR Data Science Refinery provides scalable data science tools to organizations to help them generate insights from their data and convert them into operational applications. It provides an access to all platform assets including app servers, web servers, and other client nodes and apps. The MapR Data Science Refinery also comes with 8 visualization libraries, including MatPlotLib and GGPlot2.
  • In addition, Apache Spark connectors are provided for interacting with both MapR-DB and MapR-ES. MapR also includes a preconfigured Docker Container to use MapR as a data store. The Stateful Containers offer easy deployment solutions apart from being secure and extensible.
  • Organizations can also create real-time pipelines for machine learning applications and apply ML models to real-time data by the native integration between MapR-ES and ML libraries.
  • In addition, The MapR platform 6.0 also includes single-click security enhancements, cloud-scale multi-tenancy, and MapR volume metrics, available via an extensible volume dashboard in Grafana.  

The MapR Platform 6.0 is available now. However, for Cloud providers such as Microsoft Azure, Amazon Web Services, and Oracle Cloud, the version 6.0 would be available before the end of this year.

For more information about the product, you can visit the official documentation here.

Content Marketing Editor at Packt Hub. I blog about new and upcoming tech trends ranging from Data science, Web development, Programming, Cloud & Networking, IoT, Security and Game development.


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