Following the launch of version 3.7.4 of the Striim platform, insideBIGDATA published an article highlighting the key updates, most notably the bolstering of its ease of use, connectivity, manageability and scalability for delivering streaming analytics applications involving Apache Kafka. While SQL-based integration with Kafka has been available for previous product releases, 3.7.4 includes utilities to help users quickly and easily scale Kafka applications by gathering baseline performance metrics for real world applications that involve parsing, formatting, buffer management and external connectivity.
Regarding this further integration with Apache Kafka, Alok Pareek, Co-founder and EVP of Products at Striim, is quoted in the piece saying, “It’s a daunting challenge, integrating multiple tiers when building Streaming Applications with Kafka as an underlying message store. Striim makes that problem go away. For several years, Striim has been the leader in defining an integrated Streaming Data Platform that includes not just Kafka, but also SQL-based applications and universal connectivity with a wide variety of event delivery semantics. With the 3.74 release, we have added Kafka diagnostic utilities, advanced monitoring metrics, and additional connectors to reduce the complexity of managing Kafka in production environments.”
Read the full article, “End-to-End, SQL-based Streaming Data Platform Simplifies and Speeds Delivery of Kafka-driven Analytics Applications.”