An Intellyx Brain Candy Brief
When we last spoke with Rockset in March 2022, the company offered a real-time analytics database centered on its converged index that included search, row, and column indices that operated simultaneously in real-time. The result was fast SQL-based analytics on real-time data.
Today, Rockset competes favorably in the real-time search market because it neither requires a time-consuming denormalizing step nor reindexing upon changes to individual fields.
Rockset has also added compute-compute separation to its architecture, running reads and writes on separate clusters of instances to avoid resource contention among them. As a result, Rockset doesn’t require the costly overprovisioning of alternative search technologies.
The company also added vector indexing to support real-time vector searches, useful for performing similarity searches across multiple criteria (aka dimensions).
Similarity searches are important for eCommerce recommendation engines, real-time matching algorithms for ride hailing and online dating apps, etc. Rockset’s indexing technology improves the performance of such real-time applications.
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