StreamAnalytix Releases 2.0 with support for Apache Spark Streaming

We feel proud to unharness StreamAnalytix 2.0 - the industry's only multi-engine RTSA platform!

With a established product supported Apache Storm, StreamAnalytix has taken an enormous success with the discharge of the merchandise version 2.0 that additionally supports Apache Spark Streaming.

Why Multi-Engine?

Real-time analytics use-cases, today, area unit best optimized by utilizing completely different stream process paradigms. Some use-cases need low latency, homeless process of time-series data in motion or on the wing in an exceedingly distributed fashion, with a reliable and/or lasting data source (like Apache Kafka), that Apache Storm may address well. In alternative use-cases where a stateful, reliable, small batched, complicated process is concerned, Apache Spark Streaming is that the best match.

Clearly, real time analytics isn't a real one-size-fits-all approach which will result best in performance, tractability and time-to-market. What works for one, might not work best for another!

StreamAnalytix 2.0 simplifies the trade-off by desegregation multiple engines in an exceedingly single platform. you'll currently run your applications on a stream process engine of alternative and not compulsion, looking on the use-case necessities, and without concern about the underlying technology. Thus, we offer a replacement level of "best-of-breed" flexibility in your enterprise real-time architecture.

We've one thing to supply for everybody during this release:

As a Developer, you get a wide variety of built-in sources and sinks including TIBCO, ActiveMQ, IBM MQ, Amazon Kinesis and S3, and can extend the list with reusable custom operators. With features such as Sub-system Integration, you can easily interconnect multiple sub-systems which individually use different streaming engines, and Pipeline Versioning feature allows you to version a subsystem and rollback to a previous version any-time.

Data Scientists will increase their potency by using drag-and-drop operators for Predictive Analytics, MLLib, SparkSQL, Spark Data Transformation and a rich library of data processing functions. They will produce models within the UI, check the model output visually, and refine it by mixing streaming data with static - terribly simply, with none cryptography.

For IT Admin, we've made some core improvements in areas like Management, Monitoring and Configuration. Enhanced multi-tenancy controls now come with the ability to restrict resources for specific tenants and sub-systems.

Last but not the least, Business users will analyze the streaming data with all improved Real time Dashboards pre-configured with advance charts and graphs. With StreamAnalytix 2.0, we tend to in. nearer towards our goal to be a 'zero-code' platform and lead the wave of 'build applications with clicks, not code'. For more information please visit: www.streamanalytix.com