MapR-XD Extends Converged Data Platform to Create Cloud-scale Data Fabric

MapR Technologies, Inc., provider of a converged data platform that integrates analytics with operational processes in real time, has announced MapR-XD, a cloud-scale data store to manage files and containers. As part of the MapR Converged Data Platform, MapR-XD supports any data type from the edge to the data center and multiple cloud environments with automatic policy-driven tiering from hot, warm or cold data to enable customers to create global data fabrics which are ready for analytical and operational applications.

According to MapR, storage and data management are in-the-midst of a “generational re-platforming” to move forward into the data age.  Key shifts are underway in storage and data management driven by the economics of flash and NVME technologies, the adoption of clouds and IoT at the edge, evolving use cases and workloads, new demands imposed by deep learning technologies, and the radical change in scale and types of data.

By providing a robust solution to manage data movement across multiple locations with security, high performance and multi-tenancy, MapR is providing a strategic solution for enterprises embarking on crafting and implementing a next gen data strategy, said Anil Gadre, chief product officer, MapR Technologies.  The converged data platform enables a data fabric with a global view of data and metadata, supporting a wide diversity of data types for both analytics and operations. 

According to MapR, the new MapR-XD Cloud-scale Data Store includes:

  • Files, Container Support - MapR-XD provides unified security, data protection and high availability across diverse data types.  The same underlying data can be accessed through industry standard APIs, including NFS, POSIX and HDFS to simplify development, administration and eliminate data sprawl.
  • Global Exabyte Scale - MapR-XD scales to support trillions of files, exabytes of data, on thousands of commodity servers or cloud instances, which are accessible through a single global namespace. Additionally, it reduces operational complexity and provides a single, scalable view of resources, simplifying access for users, applications and containers.
  • Cloud-grade Reliability - MapR-XD delivers high availability, data protection and disaster recovery with no single points of failure, fully distributed metadata, point-in-time snapshots and high-performance, distributed mirroring.
  • Speed at Scale with Flash - MapR-XD utilizes network interconnects and takes advantage of the available performance of underlying heterogeneous hardware, such as disk and flash to meet the demands of GPU-based architectures. Automated capabilities, such as logical partitioning, parallel processing for disparate workloads, and bottleneck avoidance with I/O shaping and optimizations, ensure maximum performance across a cluster. MapR-XD includes a high-performance POSIX Client that provides up to 10x the performance of a typical NFS gateway.
  • Stateful Persistence for Containerized Applications - MapR-XD includes a secure, optimized container client for providing containers with access to persisted data. The client supports both legacy and new containerized event-based microservices applications; multiple data types of files, containers, database and event streams; works with multiple schedulers such as kubernetes, mesos and docker swarm; and across any infrastructure such as on-premises, multiple clouds and edge.   
  • Flexibility to Leverage Multiple Infrastructures - MapR-XD supports edge, on-premises and cloud environments with the same platform. It enables multi-temperature capabilities across flash, disk and cloud tiers with support for containers and automated data movement to address performance, cost and compliance concerns.
  • IoT Edge Made Easy - MapR-XD for the edge provides the ability to deploy processing and storage capabilities close to an IoT data source, such as in a car, medical device or jet engine.  MapR-XD can store and process machine or sensor-generated data for seamless integration with a centralized Converged Data Platform where global aggregation and analysis would be performed.
  • Extensible Architecture - MapR-XD is a component of the MapR Converged Data Platform, enabling customers to leverage additional capabilities, including database, stream processing and integrated analytics on the same platform.

 For more information, go here.