The benefits of programmable acceleration hardware unite with caching technology to lower the total cost of ownership of scaling Spark clusters by 80% or more.
“Infinite horizontal scaling” has been the default expansion paradigm for Spark and Hadoop. But new innovation has opened up far more efficient and cost-effective approaches to gaining performance.
Acceleration 2.0 leverages Acceleration, Caching, and the synergies between them.
Jobs run up to 10X faster without changing your Apache Spark code, increasing data science productivity and the ability to meet tight SLAs
Incorporate fuller data sets and more data sources by eliminating the bottlenecks forcing you to make compromises
Instead of scale-out and scale-up, optimize your existing Spark environment with Bigstream, lowering hardware and operating expenses
