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 including Microsoft Azure HDInsight and Amazon Kinesis
PALO ALTO, CA — January 16, 2018 — Striim, Inc., provider of the leading real-time data integration and streaming analytics platform, today announced that it has launched version 3.8 of the Striim™ platform, enhancing the scalability and ease-of-use of its streaming integration and SQL-based stream processing capabilities for Apache Kafka. New features such as multi-threaded delivery into Kafka, and an enhanced reader for Kafka with automated mapping of partitions, enable dramatic increases in performance and productivity. Version 3.8 also expands its cloud integration offering with the ability to 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, before delivering 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 further added new features that deliver multi-fold 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.
“Many Apache Kafka users among the Fortune 500 use Striim technology to provide high throughput real-time integration for cloud adoption and data lake construction. Striim’s in-memory SQL streaming analytics capability allows for preprocessing, visualization and analysis of data that’s moving through Kafka queues. The enterprise-grade nature of the Striim platform helps reduce complexity with data delivery guarantees with high performance, security, reliability, and manageability in production environments,” stated Alok Pareek, co-founder and EVP of Products at Striim. “With the release of 3.8, Striim offers unique features that make streaming data ingestion and SQL-processing on Kafka significantly faster and easier.”
Striim remains focused on facilitating cloud integration across a broad range of cloud environments. With this latest release, users are now able to integrate real-time data directly into Microsoft Azure HDInsight to support Hadoop and Kafka implementations on Azure. In addition, 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 multi-threaded delivery with automated thread management. Version 3.8 can also integrate real-time data directly into Amazon Kinesis to support stream processing in AWS.
Striim has also introduced improved data exploration by enabling users to search streaming data and compare real-time and historical data, without requiring coding. These new features enable business users to quickly and easily identify critical and unusual trends via the live dashboards. Striim further offers the ability to embed Striim charts into custom web sites, allowing users to easily share Striim data and insights to users across the enterprise.
Notably in this latest release, Striim also announces 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. Read more in the related press release, “Striim Offers Data Pseudonymization for GDPR Compliance.”
For more information regarding version 3.8 of the Striim platform, including enhancements for Apache Kafka, cloud integration, data exploration, and GDPR compliance, please read the related blog post, or download the Striim platform for free.
The Striim™ (pronounced “stream”) platform is an enterprise-grade streaming integration solution. The platform makes it easy to ingest and process high volumes of streaming data – including change data capture – for real-time log correlation, cloud integration, edge processing, and streaming analytics. Companies worldwide use the Striim platform to deliver real-time data integration, analysis and visualization for a wide variety of use cases including data security, fraud, SLA monitoring, customer experience, replication, data modernization, and Internet of Things (IoT) analytics. Please visit striim2020.local.com, read our blog at striim2020.local.com/blog, follow @striimteam, or download the Striim platform.