Game-changing economics for Apache Spark clusters
July 30, 2021 - Watch recording
Abstract
Bigstream’s new Acceleration 2.0 solution allows you to upgrade your Apache Spark cluster 80% less expensively than the way most organizations expand today.
Big data systems have thrived because of the ability to spread large data workloads across many computing nodes. Apache Spark is a leading example, with a fast developing open-source based platform that optimizes across large clusters of computers. The promise of infinite horizontal scaling is appealing, imagining that any capacity or performance obstacle can be met by adding more servers to your cluster.
In this webinar recording, we discuss the limitations of this perspective and the resulting inefficiency and overspending. We introduce better ways to scale a big data platform. Hardware and software acceleration technology can turbo boost an existing Spark cluster and do so much faster than a traditional scale-out project. With Bigstream’s latest Acceleration 2.0 technology we present game-changing economics, reducing the total cost of ownership of Spark expansion by over 80%!

Brad Kashani
Chief Executive Officer, Bigstream
Brad is Bigstream's Chief Executive Officer. Prior to Bigstream, Brad has had executive leadership roles at Juniper Networks, Procket Networks, and Cisco systems, where he created and led global functions in sales and services.

Bishwa Roop Ganguly
Chief Solution Architect, Bigstream
Bishwa Roop Ganguly is Chief Solutions Architect at Bigstream. He has a PhD in Electrical Engineering from MIT, and an MS and BS in Computer Science from University of Illinois and University of California at Berkeley, respectively. He has published extensively in the field of parallel processing and computer networks. He also has 5 years of experience as a Data Scientist using Hadoop, Spark and SQL. He currently manages customer and partner engagements at Bigstream.