Author: Nikhil Marrapu

A major bottleneck for controlling Apache Spark costs or scaling analytics and AI workloads is Spark’s hard dependency on traditional CPU-only infrastructure. In this post, learn how DataPelago Accelerator for Spark closes that gap by seamlessly running your Spark workloads on heterogeneous hardware, delivering up to 10 times faster execution and up to 80% lower costs with zero code changes, no data migration, and no disruption to existing security configurations. See production results across social media, ecommerce, and financial services customers as you find out how to run a proof of concept on your own workloads.