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 ...

In this manner, Lambda satisfied the data processing needs for a certain class of applications that valued high-throughput, low-latency, fault-tolerance, and data accuracy. Many organizations—in ...

Streaming data, also called event stream processing, is usually discussed in the context of big data. It is data that is generated continuously, often by thousands of data sources, such as sensors ...

As AI shifts from experimental phases to mission-critical roles—such as fraud detection, live recommendation engines, and real-time video analytics—the traditional batch-first data processing approach ...

Lambda architecture has been a popular solution that combines batch and stream processing. Kartik Paramasivam at LinkedIn wrote about how his team addressed stream processing and Lambda ...

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.

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 ...

Today’s episode of “The Interview” with The Next Platform is focused on the evolution of stream processing—from the early days to more recent times with vast volumes of social, financial, and other ...