Striim Enhances SQL-Based Stream Processing for Apache Kafka

Version 3.8 adds multi-threaded delivery into Kafka; expands real-time data integration into cloud environments

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Striim, Inc., a real-time data integration and streaming analytics platform vendor, has released version 3.8 of its Striim platform.  The update enhances the scalability and ease of use of its streaming integration and SQL-based stream processing capabilities for Apache Kafka and adds multi-threaded delivery into Kafka and an enhanced reader for Kafka with automated mapping of partitions, enabling dramatic increases in performance and productivity. Version 3.8 also expands its cloud integration offering that can capture real-time data from Amazon S3 and integrate real-time data into Azure HDInsight and Amazon Kinesis.

Apache Kafka users leverage the Striim platform to continuously collect real-time data from enterprise databases, logs, sensors, and message queues, process data in-flight without coding, and deliver enriched and transformed data to Kafka within milliseconds. In addition, Kafka customers use the Striim software to analyze and visualize their data in real time, as it streams in Kafka, and deliver data and insights to cloud or on-premises targets.

In version 3.8, Striim has added features that deliver performance enhancements for streaming real-time data into Apache Kafka and simplify the setup for reading real-time data from Kafka message queues. The platform uses multi-threaded delivery with automated thread management and data distribution within a single Apache Kafka Writer, supporting high-throughput environments with easier scalability and significant performance increases to optimize a many-core, single-node architecture. In addition, customers can now use the Striim platform to read from Kafka queues with automated mapping of partitions, dramatically simplifying productivity and accelerating time to market. With 3.8, Striim also offers improved pipeline latency monitoring for its Kafka adapters, which helps identify bottlenecks and streamline fine-tuning for even higher performance.

Striim facilitates cloud integration across a broad range of cloud environments. With this latest release, users can integrate real-time data directly into Microsoft Azure HDInsight to support Hadoop and Kafka implementations on Azure. Amazon users can now read data from AWS S3 to share with on-premises systems and other cloud applications in real time and feed data into AWS S3 faster and at scale, leveraging new multithreaded delivery with automated thread management. Version 3.8 can integrate real-time data directly into Amazon Kinesis to support stream processing in AWS.

Striim has improved data exploration by enabling users to search streaming data and compare real-time and historical data without requiring coding, enabling business users to quickly and easily identify critical and unusual trends via the live dashboards. Striim can embed Striim charts into custom websites, allowing users to easily share Striim data and insights to users across the enterprise.

Notably in this latest release, Striim adds support for pseudonymization for GDPR compliance. The platform enables several data privacy initiatives, including data masking and real-time auditing capabilities to facilitate compliance with the impending EU regulations.

For more information regarding version 3.8 of the Striim platform, including enhancements for Apache Kafka, cloud integration, data exploration, and GDPR compliance, visit

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