SnappyData: a hybrid system for transactions, analytics, and streaming: demo

Abstract

An increasing number of applications rely on workflows that involve (1) continuous stream processing, (2) transactional and write-heavy workloads, and (3) interactive SQL analytics. These applications need to consume high-velocity streams to trigger real-time alerts, ingest them into a write-optimized store, and perform OLAP-style analytics to derive deep insight quickly. Consequently, the demand for mixed workloads has resulted in several composite data architectures, exemplified in the "lambda" architecture, requiring multiple systems to be stitched together---an exercise that can be hard, time consuming and expensive. Instead, our system, SnappyData, fulfills this promise by (i) enabling streaming, transactions and interactive analytics in a single unifying system---rather than stitching different solutions---and (ii) delivering true interactive speeds via a state-of-the-art approximate query engine that leverages a multitude of synopses as well as the full dataset.