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 ...

Real-time processing complicates tasks such as data loading, transformation, backfilling and schema changes. “All the data management problems we have already faced in batch, we are now solving ...

Data architects then reserve streaming technology for niche real-time applications that require sub-minute latencies (see fig. 1). While a familiar decision process, this thinking encourages a false ...

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 ...

“The future of analytics isn’t about choosing between streaming, batch, or real-time processing—it’s about unifying them,” said Hojjat Jafarpour, CEO of DeltaStream.

New York-based Estuary is setting out to solve this problem with a “data operations platform” that combines the benefits of “batch” and “stream” data processing pipelines. “There’s ...

With event streaming and the ability to capitalize on real-time analytics in merchant services, we tripled agent banking sales. The first step for any financial institution to improve its real-time ...

Confluent’s complete data streaming platform on Google Cloud enables organizations to stream, connect, process, and govern real-time data across cloud and hybrid environments.

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 ...