Speeding Big Data Analytics on the Cloud with In-Memory Data Accelerator
Discontinuity in big data infrastructure drives storage disaggregation, especially in companies experiencing dramatic data growth after pivoting to AI and analytics. This data growth challenge makes disaggregating storage from compute attractive because the company can scale their storage capacity to match their data growth, independent of compute. This decoupled mode allows the separation of compute and storage, enabling users to rightsize hardware for each layer. Users can buy high-end CPU and memory configurations for the compute nodes, and storage nodes can be optimized for capacity.
This whitepaper is a continuation of Unlock Big Data Analytics Efficiency with Compute and Storage Disaggregation on Intel® Platforms