Stream processing, for dummies

DataTorrent will be making it RTS core engine available under the Apache 2.0 open source license.

The firm is a player in the real-time big data analytics market.

It is also the creator of a unified ‘stream and batch processing’ platform.

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What is stream processing?

Stream processing is the in-memory, record-by-record analysis of data in motion.

Typical examples of streaming data include data from transactions, mobile devices, web clicks and event sensors.

Stream processing promises to reduce processing time and the time to take business action based on that insight.

Users can use the results of streaming analysis to created real time dashboards to detect critical business situations and take action.

Stream i.e. lots of flow – oh, they called the company DataTorrent, I get it.

I have adoption ‘issues’ though!

So I’d love to use stream processing (now that I know what it is), but I have adoption issues based upon my personal hang-ups around GUI application assembly.

Gosh, that’s tough – but hey, DataTorrent RTS 3 offers no-coding required GUI application assembly self-service real-time & historical data visualisation and a simple data ingestion & distribution application for Hadoop.

Phew – that was lucky.

Released as Project Apex, the open-source DataTorrent RTS core engine forms the foundation of DataTorrent RTS 3, now available in three editions – Community Edition, Standard Edition and Enterprise Edition

“Big data projects are often delayed or remain stuck in the proof-of-concept phase as Hadoop can be unfamiliar and difficult to use for many enterprises”, said Nik Rouda, senior analyst, ESG, “DataTorrent RTS 3 addressed common challenges with graphical tools for developers, operations teams, data scientists and business users.”

The Community Edition is designed to enable developers and innovation groups in enterprises to quickly prove out their big data streaming and batch use cases and establish a business case for an enterprise grade big data project.

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