MapR Converged Data Platform 6.0 Powers DataOps
MapR Converged Data Platform 6.0 comes with new advancements to help organizations achieve greater value from all of their data through DataOps teams. The major system update from MapR 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.
• Automatic Platform Health and Security. To simplify processing of cluster health and continuous operations, The MapR Platform now includes: ◦ New MapR Control System administers all data (volumes, tables, and streams) and monitors cluster health with metric co-relation in single pane of glass. Also includes extensible dashboards for volume metrics, including: capacity, throughput, latency, and IOPs. MapR monitoring metrics are now automatically pushed to MapR-ES to enable easy integration with enterprise systems.
◦ Recently announced database indexing in MapR-DB delivers
auto-propagation, auto-scale, and auto-management.
• 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.
• 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
multi-tenancy, 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).