Zilliz

Free tier

The Vector Lakebase for AI — real-time serving, iterative discovery, and batch analytics at hundred-billion scale

Free tier available·All audiences·API available·Open source

Key strengths

Billion-scale vector similarity searchFully managed Vector Lakebase (real-time serving, iterative discovery, batch analytics)Lake-native storage on S3 with up to 90% cost reductionFull-spectrum search (vector, full-text, JSON, geospatial, hybrid retrieval)High reliability with 99.95% uptime SLABYOC and self-hosted (Milvus open-source) deployment optionsProduction-tested across 10,000+ enterprises

Free tier + paid plans

San Francisco, USA

Founded 2017

Self-hostable

Facts verified against zilliz.com on Oct 5, 2026

Recent changes

Oct 5, 2026Open source: now available
Oct 5, 2026Plans updated: Free tier at $0 (5 GB storage, 2.5M vCUs/month, up to 5 collections). Standard from $0/month (Serverless) or from $126/GB/month (Dedicated). Enterprise from $197/month (Dedicated). Business Critical: custom pricing. BYOC available.

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Zilliz is a fully managed Vector Lakebase built on top of Milvus, its open-source vector database engine (46,000+ GitHub stars). It delivers billion-scale vector similarity search with a unified architecture that spans real-time serving, iterative discovery, and batch analytics — all on lake-native storage backed by S3, reducing infrastructure costs by up to 90%. Zilliz exposes a rich API supporting full-spectrum retrieval: dense vector, sparse/full-text, JSON filtering, geospatial, and hybrid search modes. Deployment options include Serverless (pay-per-use), Dedicated managed cloud, BYOC (Bring Your Own Cloud), and self-hosted via the open-source Milvus project. It integrates natively with AWS, Google Cloud, and Azure, and supports open table/file formats including Apache Iceberg, Lance, and Parquet. Uptime SLA is 99.95%, with production deployments across 10,000+ enterprises.

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