Stream processing, through open source technology frameworks like Apache Flink, is one of the best-suited approaches for the modern enterprise to take the leap forward and become real time. Stream ...

Hybrid processing combines both methods and reaps the benefits of both. In general, the data is processed as a stream and simultaneously branched off to storage for later batch processing.

Acting on stream processing data. In the short term, stream processing provides the instant information needed to support analysis and decision-making on the fly.

Stream processing applications ingest events as they arrive. Depending on the business logic, events or intermediate results need to be stored for later processing.

Streaming data is hot, and open source stream processing platform Apache Kafka is growing in popularity, significantly. In this guest post, Neha Narkede, CTO and co-founder of Confluent (the ...

Decodable, the well-funded real-time data engineering and stream processing platform based, in part, on the Apache Flink open source project, is launching a major update today that aims to make ...

Stream processors are well suited for traditional GPU-focused tasks such as image, video and signal processing. It is becoming increasingly common, however, to also utilize the stream processors ...