“StreamAnalytix provides an excellent solution for streaming analytics that combines the strengths of open source with the reliability, manageability, and support of an enterprise solution” – reads the Report.
StreamAnalytix is going places. And we can’t be more excited about it.
Bloor Research recognized StreamAnalytix as one of the key challengers to the streaming analytics platforms available in the market. The report evaluated the top streaming analytics platforms like IBM, Software AG, SAS, SQLStream, and DataTorrent using various metrics. The table below shows the rating received by StreamAnalytix.
StreamAnalytix rating on various parameters by Bloor Research
“One of the major strengths of StreamAnalytix: the ability to interact with a multitude of different types of analytics (event, batch, micro-batch) and streaming engines (Spark, Storm, Flink) using the same interface and applications.” – Daniel Howard, Bloor Research
Market map of streaming analytics platform
The report validates our focus on the use of popular open source big data technologies such as Apache Spark and Apache Storm for real-time data insight. StreamAnalytix has also been recognized by Forrester, Aragon Research, Gartner, and Datanami in the past.
With a powerful visual IDE and 150+ drag-and-drop Apache Spark operators, StreamAnalytix can build and run Apache Spark based big data, stream processing, and machine learning applications up-to 10x faster than hand coding.
The platform provides end-to-end, 360-degree data processing, including ingestion, cleansing, transformation, blending, loading and visualization (via real-time dashboards), and analytics.
StreamAnalytix also offers a Lite Edition, a free standalone version which brings all capabilities required for development and life-cycle management of Apache Spark applications in both streaming and batch mode, to your desktop.
An Easy Approach to ETL with Apache Spark – Visually prepare, integrate, and transform data as it arrives
2019-03-08 23:30:00 - 10:00 am PT / 1:00 pm ET