One Platform for Big Data Applications
With MapR, data does not need to be moved to specialized silos for processing; data can be processed in place. In fact, we have applied the concept of "Polyglot Persistence" to the MapR Platform, with the ability to leverage multiple data types and formats directly, depending on your use case. The MapR Converged Data Platform enables direct processing of files, tables, and event streams. The MapR Platform also makes it easier to leverage existing applications and solutions by supporting POSIX-compliant, industry-standard NFS. Additionally, containerized applications can make use of the MapR Persistent Application Client Containers to securely access and leverage MapR platform services (MapR-FS, MapR-DB, MapR Streams) as a persistent data store.
Additional features to support a diverse set of applications and users include a range of enterprise-grade features: unified security, global namespace, high availability, data protection and disaster recovery support; multi-tenancy and volume support; data and job placement control so applications can be selectively executed in a cluster to take advantage of faster CPUs or SSD drives; and support for a heterogeneous hardware cluster.
MapR sets MinuteSort record using Google Compute Engine and MapR Distribution for Apache Hadoop
MapR and the Easiest Access to Hadoop Data
A Quick Video Explanation of MapR-DB
A Quick Video Explanation of MapR Streams
- Utility-grade reliability with self-healing, no single point of failure architecture
- Out-of-box integration with popular stream processing frameworks like Spark Streaming, Storm, Flink, and Apex
- Kafka API for real-time producers and consumers for easy application migration