SANTA CLARA, Calif.--(BUSINESS WIRE)--MapR® Technologies, Inc., provider of the industry's next generation data platform for AI and Analytics, today announced the immediate availability of MapR Ecosystem Pack (MEP) 6.1, giving developers and data scientists maximum flexibility in how they access data and build powerful AI/ML, real-time analytics and stateful containerized applications. With the release of MEP 6.1, MapR expands on the Kafka ecosystem, adds new language support for the MapR document database and support for Container Storage Interface (CSI).
MEP 6.1 further delivers on the need to enable consumption of data by the broadest possible set of applications and tools with new capabilities, including:
- Implementation of Container Storage Interface (CSI) for Kubernetes delivers persistent storage for compute running in Kubernetes-managed containers. This future-proofs Kubernetes+Storage deployments. Unlike the Kubernetes Flexvol-based volume plugin, storage is no longer tightly coupled or dependent on Kubernetes releases. This creates greater stability because the storage interface is decoupled entirely from critical Kubernetes components allowing separation of privileges as CSI components do not need full privileges of Kubernetes components. With the implementation of Container Storage Interface (CSI), persistent data layer for Kubernetes and other Container Orchestration (CO) tools, such as Mesos and Docker Swarm are now future-proofed.
- MapR Event Store for Apache Kafka: Kafka Schema Registry allows the structure of streams data to be formally defined and stored, letting data consumers better understand data producers. This registry also provides centralized schema management and compatibility checks as schemas evolve.
- MapR Database: New language bindings for Go, C# enable developers to build a broader set of new applications in the language of their choice on MapR document database. Languages include Java, Python, Node.JS and now expanding to Go, C# languages support. New language bindings provide enhanced developer productivity on MapR Database and builds on the gRPC based thin client architecture and fully native language bindings with no dependencies.
- Apache Drill 1.15 includes an enhanced S3 Storage Plugin with the ability to query next generation pcap format - pcap-ng, improved SQL compliance and performance for BI/Analytics with numerous SQL Joins related enhancements, and enhanced Parquet performance with filter pushdown. The latest release also has a simplified user experience for Drill administration and query performance analysis.
- Oozie 5.1 enhancements move dependency from Tomcat to Jetty for embedded webserver which is much more lightweight and secure and update the launcher of Oozie which is generic to YARN, instead of in the MapReduce format.
“MapR was first in our space to solve the stateful container challenge - first with Persistent Application Client Containers (PACC) for Docker containers, then with Flex-volume driver for Kubernetes,” said Suzy Visvanathan, director, product management, MapR. “Today we are thrilled to extend our lead with the implementation of CSI, helping developers and administrators alike achieve greater independence between Kubernetes releases and underlying storage. The CSI Driver leverages MapR volumes to provide a scalable, distributed persistent storage for stateful applications. Storage is no longer tightly coupled or interdependent with Kubernetes releases. Implementation of CSI provides a persistent data layer for Kubernetes and other Container Orchestration (CO) tools, such as Mesos and Docker Swarm.”
Released on a quarterly basis, MEPs ensure that customers are given quick access to the latest open source innovations. MEPs also ensure that these innovations run in supported configurations with the MapR Data Platform and other interconnected projects, greatly simplifying and error-proofing customers’ upgrade path.
MEP 6.1 is immediately available.
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MapR Technologies, provider of the industry’s next generation data platform for AI and Analytics, enables enterprises to inject analytics into their business processes to increase revenue, reduce costs, and mitigate risks. MapR addresses the data complexities of high-scale and mission critical distributed processing from the cloud to the edge, IoT analytics, and container persistence. Global 2000 enterprises trust the MapR Data Platform to help them solve their most complex AI and analytics challenges. Amazon, Cisco, Google, Microsoft, SAP and other leading businesses are all part of the MapR ecosystem. For more information, visit mapr.com.
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