Streaming data records are typically small, measured in mere kilobytes, but the stream often goes on and on without ever stopping. Streaming data, also called event stream processing, is usually ...

Stream processing turns this paradigm around: the application logic, analytics, and queries exist continuously, and data flows through them in a continuous way. Upon receiving an event from the stream ...

This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and ...

The value of streaming data is less about its movement and more about what you can do with it at that moment in time—or how you can process it.

Atlas Stream Processing, a solution that aggregates and enriches streams of high velocity, rapidly changing event data, and unifies working with data, is now in public preview.

Real-time stream processing isn’t a new concept, but it’s experiencing renewed interest from organizations tasked with finding ways to quickly process large volumes of streaming data. Luckily for you, ...

Data stream processing is defined as a system performing transformations for creating analytics on data inside a stream. In Part 1 of this series, we defined data streaming to provide an understanding ...

RisingWave Labs, a company building a platform for streaming data processing, today announced that it raised 36 million in venture funding.

RisingWave has raised $36 million with a streaming database that combines elements of traditional databases and stream processing.

Real-time data streaming is still early in its adoption, but over the next few years organizations with successful rollouts will gain a competitive advantage ...