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 ...

Reduced Cost: Data streaming for business is already processed and analysed, they do not have to invest in warehousing or storage of data. Along with this, the costing for analysis is saved too. Also, ...

Streaming data — also called real-time data — is information that arrives continuously from various sources and is analyzed quickly so businesses can respond in near-real time to events on the ...

The value of streaming data is less about its movement and more about what you can do with it at that moment in time—or how you can process it.

Big data is a moving target, and it comes in waves: before the dust from each wave has settled, new waves in data processing paradigms rise. Streaming, aka real-time / unbounded data processing ...

In this first installment of a three-part series on data streaming, Apache Kafka, and data analytics, we will dive into fully explaining data transaction streaming and the technologies that make it ...

Spark Streaming was added to Apache Spark in 2013, an extension of the core Spark API that allows data engineers and data scientists to process real-time data from various sources like Kafka, Flume, ...

The future of the future: Spark, big data insights, streaming and deep learning in the cloud Apache Spark is hailed as being Hadoop's successor, claiming its throne as the hottest Big Data platform.