Efficient resource scheduling and shared infrastructure results in shorter application wait times, higher throughput and faster analytics.
Maximize usage of resources and eliminate silos of resources that would otherwise each be tied to multiple instances and different versions of Spark and other applications.
Production-proven at scale. Supporting 100s of application & frameworks ~5k hosts, 150k cores & >1B tasks/day, on-premises & clouds.
A multitenant solution, end-to-end security and runtime isolation. Spark and application lifecycle management. IBM support and services.
Consolidated framework for deploying, managing, monitoring, and reporting reduces administrative overhead.
The included Spark distribution makes it easy to deploy a full analytics environment both for exploratory projects and production.