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Confluent Releases KSQL, a Streaming SQL Engine for Apache Kafka

By   /  August 29, 2017  /  No Comments

by Angela Guess

A new press release reports, “Confluent, provider of the leading streaming platform based on Apache KafkaTM, today announced KSQL, an open source streaming SQL engine that enables continuous, interactive queries on Apache Kafka. In today’s event-driven world, businesses need to respond to the continuous streams of data that are the source of truth for everything happening within the company. With KSQL, any developer that knows SQL can leverage real-time data. Unlike other stream processing engines that require complex infrastructure or mastery of various programming languages, KSQL gives the user a familiar syntax in an easy-to-manage-and-build solution, while benefiting from Kafka’s distributed, scalable and reliable development and production history.”

The release goes on, “Common examples of stream processing might include comparing two or more streams of data to understand anomalies and respond to them in real time or transforming data as it’s ingested to better suit downstream consumers. Stream processing can be used to identify fraud by financial services companies, monitor out-of-bounds system performance metrics, and much more. Other common uses include: (1) Anomaly Detection: Pattern recognition and anomaly detection are real-time and event-driven processes ideally suited to running against streams of data. This can be used horizontally across a number of industries and use cases, for example: financial institutions can alert a bank’s users of out-of-the-ordinary transactions, while potentially detecting a security attack. (2) Monitoring: Business are able to move from batch systems to real-time notifications and catch issues in real time that can prevent entire system failures. With KSQL, teams can leverage SQL-like queries to solve problems through the use of a widely-known language while errors are happening, rather than waiting until the next day.”

Read more at Business Wire.

Photo credit: Confluent

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