Streaming data platforms ingest, process, transform, analyze, and render action from streaming data in real time. The best tools can do so before data is written to a database, to support use cases requiring low latency. This technology has become imperative because of the influx of sensor data, data generated from the internet, and data continually produced by applications across a host of industry verticals, including customer-facing ones.
These developments are responsible for the pace of business—and the data management requisites for facilitating it—accelerating to real-time processing that completely outclasses time-consuming, traditional batch processing. Consequently, streaming data platforms are indispensable to an array of user segments, including business end users (such as stock traders, portfolio managers, and health care practitioners), IT and operations personnel monitoring telemetry data and other data types, and data scientists building and refining machine learning (ML) models.
