Rockset Unveils Real-Time SQL Analytics for Raw Events from Apache Kafka

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According to a new press release, “Rockset, the serverless search and analytics company that enables SQL on NoSQL data, today announced the capability to analyze raw events from Apache Kafka in real time. Kafka, backed by Confluent, is one of the most popular distributed streaming platforms and capable of handling trillions of events a day. Rockset takes an entirely new approach to ingesting, analyzing and serving data so that developers and business stakeholders can run powerful SQL analytics, including joins, on raw event data from Kafka. With this release, Rockset is also announcing a partnership with Confluent, with Rockset’s Kafka Connect Plugin listed as a Verified Gold Connector in Confluent Hub.”

The release goes on, “Increasingly, businesses are capturing real-time data to drive intelligent actions on the fly. However, traditional databases are not built to handle semi-structured data, making it difficult to operationalize event data like this in real time. In an effort to solve this issue and unlock analytics, considerable data engineering effort goes into building complex data pipelines that schematize and load NoSQL data from Kafka event streams into SQL-based systems. These pipelines are difficult to build, expensive to maintain and hours behind in terms of insights into events – making “real-time” operational analytics on event data next to impossible.”

It adds, “Rockset complements Kafka’s KSQL stream processing capabilities by serving as the ‘sink’ that ingests the processed stream. With Rockset, new event data from Kafka is automatically represented as a dynamic SQL table and available for querying in seconds. Rockset uses Converged Indexing™ and a Distributed SQL Processing Engine under the hood to enable customers to filter, aggregate and join across different datasets from different sources in milliseconds, without upfront schema definitions.”


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