It wouldn’t be Christmas without some big spending! IBM’s acquisition of Confluent could address some critical gaps for Big Blue and support customers moving away from batch processing, in search of usable AI.

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As enterprises increasingly rely on both real-time and historical data to drive business impact, the need to unify batch and streaming analytics has never been greater. According to IDC, the stream data processing market is expected to grow over the next ...

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 discussed in the context of big data. It is data that is ...

On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data New private networking and security features make stream processing more secure and enterprise-ready ...

Let the OSS Enterprise newsletter guide your open source journey! Sign up here. Data may well be world’s most valuable resource today, given the role it plays in driving all manner of business decisions. But combining data from SaaS applications and ...

Developers are always looking for Big Data tools to make it faster and easier to build applications, with Hadoop as a preferred solution for storing and processing the data. Given that Big Data is on the verge of widespread adoption, creating applications ...

In batch processing, if costs are not isolated, high-volume customers and products tend to subsidize lower-volume ones. This article reviews different types of batch activities and how they would be handled under traditional costing and two different ...