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 ...
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 ...
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 ...
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 ...
Apache Kafka, the open-source distributed messaging system, has steadily carved a foothold as the de facto real-time standard for brokering messages in scale-out environments. And if you think you ...
When the big data movement started it was mostly focused on batch processing. Distributed data storage and querying tools like MapReduce, Hive, and Pig were all designed to process data in batches ...
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 ...
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