Abstract: Data stream processing holds great potential value in lots of practical application scenarios. This paper studies two new but important patterns for items in data streams, called promising ...

IBM is betting $11 billion that real-time data infrastructure will become as critical to AI deployments as databases were to enterprise applications. The company's just-announced acquisition of ...

Since the early 2000s, ultra-wideband (UWB) technology has gradually found its way into a variety of commercial applications that require secure and fine-ranging capabilities. Well-known examples are ...

Confluent has launched Streaming Agents to embed AI directly into data streams, addressing the enterprise challenge of moving AI agents from prototype to production by providing real-time data access ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

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 ...

Confluent has unveiled new capabilities that unite batch and stream processing to enable more effective AI applications and agents. The aim? Confluent wants to position itself as an essential platform ...

The developer community is “getting its feet under us” with data streaming, but the transition will require organisations to create well-managed data products, Confluent’s vice-president of developer ...

Data streaming has emerged as a critical component of modern data architectures, enabling organizations to process and analyze information in real-time. This comprehensive guide explores the ...

Several key trends are shaping the data streaming landscape in 2025, including AI-powered stream processing, enhanced privacy and security measures, the rise of edge computing and distributed ...