New integration enables real-time analytics for Oracle databases, with sub-second search, aggregations and joins

 Rockset, the Real-time Analytics Platform Built for the Cloud, announced a new integration with Oracle, enabling developers to run real-time, search, aggregations and joins on data from Oracle databases.

Today, more organizations are investing in real-time analytics as the foundation for digital, particularly in areas like e-commerce, logistics and delivery tracking, gaming leaderboards, fraud detection systems, health and fitness trackers, and recommendation engines.

“Enterprises looking to use data from their Oracle databases to power user-facing analytics have traditionally relied on read replicas that are too expensive, or loaded it into warehouses that are too slow,” said Shruti Bhat, Chief Product Officer at Rockset. “Rockset now ingests real-time change data capture (CDC) streams from Oracle, and indexes every field to enable low latency, high concurrency analytics, without the cost and complexity of traditional approaches.”

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As the world moves from batch to real-time analytics, this release enables developers using Oracle to:

• Run sub-second analytical queries, including JOINS with other databases, lakes, or event streams.
• Achieve better database performance by isolating analytical queries on Rockset, which in turn scales horizontally in the cloud.
• Power fast microservices using developer SDKs or deliver real-time reporting using one of Rockset’s integrations with visualization tools including Tableau, Retool, Redash, and Superset.

Built by the team behind the online data infrastructure that powers Facebook Newsfeed and Search, Rockset is inspired by the same indexing systems that power real-time analytics at cloud scale. As new data is ingested in real-time, Rockset allows continuous transformations and rollups without the need for batch ETL jobs. The data is automatically indexed in a Converged Index™, delivering fast search, aggregations and joins on real-time data, with cloud-native speed and scale.

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