As more and more organizations have come to rely on streaming data to provide real-time insights, a number of applications have sprung up to handle the myriad technical challenges that streaming data ...

AI workflows fundamentally depend on real-time data movement: ingesting training data streams, feeding live data to models for inference and distributing predictions back to applications. But strip ...

Analytics is often described as one of the biggest challenges associated with big data, but even before that step can happen, data has to be ingested and made available to enterprise users. That’s ...

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...

Streaming is hot. The demand for real-time data processing is rising, and streaming vendors are proliferating and competing. Apache Kafka is a key component in many data pipeline architectures, mostly ...

Organizations building real-time stream processing systems on Apache Kafka will be able to trust the platform to deliver each messages exactly once when they adopt new Kafka technology planned to be ...

These days, massively scalable pub/sub messaging is virtually synonymous with Apache Kafka. Apache Kafka continues to be the rock-solid, open-source, go-to choice for distributed streaming ...

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