This release of The Kinetica Streaming Data Warehouse serves the most demanding enterprise requirements, including best-in-class security, resiliency, and ad hoc analytics on petabyte-scale data sets.

FanDuel Sports Network is getting in on the total audience delivery trend, moving to a metric combining linear and streaming ...

ThatDot, which offers a software platform for complex event processing, today released its open-source platform Quine.

Spark already addressed fast batch analytics, but support for streaming was previously limited to micro-batch (meaning up to seconds of latency) until last February's Spark 2.0 release.

What is the role of video streaming data analytics in data science space. Learn how to implement a motion detection use case using a sample application based on OpenCV, Kafka and Spark Technologies.

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 ...

Analyzing real-time streaming data remains one of the biggest challenges in business analytics. The demand for event-stream processing and analytics capabilities is growing as businesses look for ...

By combining streaming, location, and machine learning analytics into a unified platform, the streaming data warehouse actually untangles a data architecture.

Amazon’s AWS cloud computing platform today launched Kinesis Analytics, a new service that makes it easier to analyze real-time streaming data with the help of standard SQL queries. Kinesis ...

A living application doesn’t need to store data any more than a living organism needs to “store” its blood. Streaming data analytics is in fact the bloodstream of modern applications. In ...