Batch processing, a long-established model, involves accumulating data and processing it in periodic batches upon receiving user query requests. Stream processing, on the other hand, continuously ...

1. Treating Data Streaming Like Accelerated Batch Processing One costly mistake in adopting data streaming is treating it like accelerated batch processing. Companies collect data in chunks before ...

They are processing streaming data and solving business requirements faster and with higher value. Like in many cases, early adopters are likely to be the winners and trendsetters in their industries.

International Data Corp. has forecast that the stream processing market will grow at a compound annual growth rate of 21.5% through 2028, driven by increased data velocity, real-time analytics and ...

Apache Storm Apache Storm is a distributed stream processing framework that was created by Nathan Marz about a decade ago to provide a more elegant way to process large amounts of incoming data. Storm ...

Confluent, Inc., the data streaming pioneer, announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries ...

Apache Beam, a unified programming model for both batch and streaming data, has graduated from the Apache Incubator to become a top-level Apache project. Aside from becoming another full-fledged ...

Confluent, Inc., the data streaming pioneer, is introducing new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, ...

RisingWave Labs, a company developing a platform for data stream processing, today announced that it raised $36 million in a Series A funding round led by Yunqi Partners, undisclosed corporate ...

Customers can choose from many pipeline sink types, including PostgreSQL, S3, ElasticSearch, ClickHouse, Rockset, and Apache Kafka. Tkachenko summarises the benefits of data streaming for blockchain: ...