Reimagine in-app search and analytics

Index your vector, text, geospatial and JSON data for the most efficient hybrid search and real-time analytics at any scale

Learn About Rockset's Hybrid Search ArchitectureRead the Whitepaper ->
Read customer stories ->

World's fastest search and analytics database

Measuring end-to-end latency with streaming ingest and high QPS workload
10MB/s
Streaming Ingest
99ms
p95 Query Latency
10000
QPS
See performance benchmark ->
vector search diagramvector search diagram

Real-time indexing

Continuously ingest data and vector embeddings with built-in connectors for Kafka, MongoDB, DynamoDB, S3, OpenAI and more. Data is stored as a Converged Index with field level upserts
4x faster ingestCompare w/ Elasticsearch->

Millisecond SQL

Use standard SQL for fast search, filtering, aggregations, joins and vector search with powerful metadata filtering that’s as simple as a WHERE clause
67% FASTER QUERIESCompare w/ Clickhouse->
20X
faster development of new features

Build real-time features in record time

Save thousands of developer hours with the flexibility of schemaless ingestion coupled with Data APIs for fast SQL search, aggregations, joins and vector search. Zero ETL, no denormalization, no managing shards, indexes or clusters.
40%
lower compute and storage cost

Scale performance, not cost

Serve multiple, isolated apps from a single real-time dataset. Scale QPS instantly, without needing additional read replicas. Scale more efficiently in the cloud with compute-storage separation and compute-compute separation.
See product page ->

For search, real-time analytics and AI apps

Whatnot logo
Rockset delivered true real-time indexing and queries that didn’t just match Elasticsearch, but did so at much lower operational effort and cost.

Emmanuel Fuentes,
Head of Machine Learning and Data Platforms