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.

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. 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.

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. 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.