Impetus Technologies, has announced StreamAnalytix 3.0, which adds support for Apache Spark-based batch processing and enriched online and offline machine learning features. The new capabilities are targeted at helping enterprises improve the performance of their analytical models and achieve more favorable business outcomes. StreamAnalytix 3.0 will be available under a beta program online by the end of April 2017.
According to the company, the new version of Stream Analytix adds to the stream processing capabilities driven by Apache Spark Streaming and Apache Storm so that data and analytics professionals can now orchestrate and visualize streaming and batch workflows in a unified platform for real-time data ingestion, processing, and advanced analytics.
"Spark Streaming has rapidly gained popularity as one of the most widely used platforms to process streaming data; however, most enterprise big data use cases today need both Spark Streaming and Spark batch," said Anand Venugopal, head of StreamAnalytix at Impetus Technologies. "Based on strong market demand, StreamAnalytix 3.0 is now able to process Spark Streaming, Spark batch and even interconnected workflows. The new debug features for development time and run time in this release are also very sought after by our Spark customers. Overall, these new abilities give enterprises convenient access to a single visual platform for analyzing both fast data and big data to deliver context-aware customer experiences, accelerate data-driven business processes and maximize operational efficiencies with real-time insights."
StreamAnalytix is an open source-based, multi-engine platform for development of real-time stream processing and machine learning applications. It provides a drag-and-drop user interface which abstracts an open source stack including Apache Kafka, Apache Spark, Apache Storm, Hadoop and NoSQL data stores. The platform is available on premise or in the cloud and enables streaming ETL, Internet of Things (IoT) and log analytics, real-time smart customer care and churn analytics, real-time fraud and anomaly detection, and predictive maintenance.
In addition to support for batch processing, with the ability to schedule batch jobs via Apache Oozie, StreamAnalytix 3.0 includes advanced machine learning capabilities such as support for A-B testing and the champion-challenger model framework.
The platform now also includes Hadoop certification with Cloudera, in addition to Hortonworks and MapR; and new data connectors for IoT, social media and clickstream, in addition to Amazon Web Services Kinesis, Amazon Web Services Simple Storage Service and TIBCO Enterprise Service Bus.
For more information, and to sign up for a free trial version, go to www.streamanalytix.com/three/beta.