1. New DataTorrent RTS Delivers Real Time Streaming Analytic Capabilities on Hadoop with Performance Greater than 1 Billion data Events Per Second
6/10/2014 12:45:39 PM
New DataTorrent RTS Delivers Real Time Streaming Analytic Capabilities on Hadoop with Performance Greater than 1 Billion data Events Per Second
Hadoop, Cloud distribution, big data, real-time analytic streaming, app analytics
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App Developer Magazine
Enterprise

New DataTorrent RTS Delivers Real Time Streaming Analytic Capabilities on Hadoop with Performance Greater than 1 Billion data Events Per Second


Tuesday, June 10, 2014

Richard Harris Richard Harris

DataTorrent, which offers an enterprise grade real-time stream processing platform on Hadoop, has announced the general availability of DataTorrent RTS which enables enterprises to take action in real-time as a result of high-performance complex processing of data as it is created. 

DataTorrent RTS delivers real-time streaming analytic capabilities on Hadoop with performance greater than 1 billion data events per second - equivalent to processing 46 cumulative hours of streaming Twitter data in one second. Additionally, DataTorrent RTS’ fault tolerant architecture ensures zero downtime and is certified to run on all major Hadoop and Cloud distributions.

DataTorrent RTS allows organizations to harness the full potential of big data by enabling faster data ingestion, data processing, and data insights. Key capabilities include:

- Streaming, scalable data ingestion & extraction from any source: DataTorrent RTS connects to thousands of systems simultaneously using pre-built operators and processes millions of incoming data events without delay.

- High performance data transformation and complex computation: In-memory processing on data and events as they happen provides near-zero latency with the ability to scale to billions of data events per second.

- Real-time monitoring, alerting and action: DataTorrent RTS’ architecture provides the ability to extend analytic capabilities beyond static queries. Custom business logic written in Java enables monitoring, alerting, analysis, and action all taken in real-time.

- Compatibility with existing Big Data processes: DataTorrent RTS archives and loads results into any data store for archiving and query-based analytics.

- Fault tolerant, highly available, dynamic system: DataTorrent RTS’ streaming window implementation allows for in-line system checkpointing to ensure high availability and guarantees processing of every event. The fault tolerant implementation provides the flexibility to change business logic and insert or delete operators on a running system with no downtime.

DataTorrent RTS is a Hadoop 2.0 (YARN) native application. One hundred percent Hadoop 2.0 compliance allows DataTorrent RTS and Hadoop Map Reduce to exist side-by-side. With more than 400 Apache 2.0 open source DataTorrent operators, creating and deploying real time streaming analytic application is now easier than ever.



Read more: https://www.datatorrent.com

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