By Sarthak Garg

StreamAnalytix Releases 2.0 with support for Apache Spark Streaming

StreamAnalytix Releases

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

With a proven product based on Apache Storm, StreamAnalytix has taken a big step forward with the release of the product version 2.0 that also supports Apache Spark Streaming.

Why Multi-Engine?

Real-time analytics use-cases, today, are best optimized by utilizing different stream processing paradigms. Some use-cases require low latency, stateless processing of time-series data in motion or in flight in a distributed fashion, with a reliable and/or durable data source (like Apache Kafka), which Apache Storm could address well. In other use-cases where a stateful, reliable, micro batched, complex processing is involved, Apache Spark Streaming is the best fit.

Clearly, real-time analytics is not a true one-size-fits-all approach that will result best in performance, manageability and time-to-market. What works for one, may not work best for another!

StreamAnalytix 2.0 simplifies the trade-off by integrating multiple engines in a single platform. You can now run your applications on a stream processing engine of choice and not compulsion, depending on the use-case requirements, and without worrying about the underlying technology. Thus, we provide a new level of "best-of-breed" flexibility in your enterprise real-time architecture.

We've something to offer for everyone in 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 can increase their efficiency by using drag-and-drop operators for Predictive Analytics, MLLib, SparkSQL, Spark Data Transformation and a rich library of data processing functions. They can create models in the UI, test the model output visually, and refine it by blending streaming data with static - very easily, without any coding.

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 can analyze the streaming data with all improved built-in Real-time Dashboards pre-configured with advance charts and graphs. With StreamAnalytix 2.0, we inch closer towards our goal to be a 'zero-code' platform and lead the wave of 'build applications with clicks, not code'.

To learn more, watch the Demo Video, download the Datasheet, or try StreamAnalytix 2.0.