Zilliz
About Zilliz
Zilliz's product stores and indexes embedding vectors for AI applications. It provides a fully managed vector database and data services for unstructured data.
Products
- Vector Lakebase: A service unifying real-time vector search, lake-scale discovery, and AI data operations.
- Milvus: An open-source vector database created by Zilliz's engineers.
Used for
- Running recommendation systems.
- Detecting anomalies.
- Searching across vector, text, JSON, and geospatial data combined with hybrid retrieval and filtering.
Who it is for
- Organizations seeking to make sense of unstructured data.
From Zilliz's own website, read 2026-10-24. How we build listings.
How to evaluate Vector Databases & RAG
This is how the CIOPages Research Team evaluates this category. It is not an assessment of Zilliz. It comes from our Vector Database & AI Search buyer guide.
25%
Retrieval Quality & Index Options
ANN algorithms offered (HNSW, IVF/IVF-PQ, DiskANN, GPU/CAGRA), achievable recall@k at your latency budget, quantization for memory savings, and whether the index supports real-time inserts or needs rebuilds
20%
Hybrid Search & Filtering at Scale
Native vector+keyword (BM25 / sparse) fusion, reranking, and — critically — in-graph metadata pre-filtering that holds recall under selective filters rather than degrading to brute force or empty result sets
20%
Scale, Performance & Freshness
Vector ceiling per node and horizontally, p95/p99 latency and QPS under your real filters, multi-tenancy and namespaces, multi-region, and how fast new or updated embeddings become queryable (insert-to-searchable lag)
15%
Operating Model & Lock-In
Managed SaaS vs. self-hosted vs. bring-your-own-cloud, license terms (Apache 2.0 / BSD vs. proprietary), data-export and migration path, and how much sync/ETL you take on if vectors live apart from the source data
10%
Security, Governance & Residency
RBAC and API-key scoping, encryption in transit and at rest, SOC 2 / ISO 27001 / GDPR posture, data residency and VPC/air-gapped options, and inherited governance (e.g. Unity Catalog, platform IAM) where applicable
10%
Developer Experience & Ecosystem
Client SDKs and API ergonomics, LangChain / LlamaIndex / framework integrations, built-in or hosted embedding and reranking, docs quality, and operational maturity (backups, observability, upgrades)
CIOPages put this listing together from public sources. It’s information, not an endorsement. How we build listings. Work here? Claim this listing or .
Quick Facts
zilliz.com Pricing pageCategoryAI & ML Platforms
SubcategoryVector Databases & RAG
We publish a detail only when we can point at the page it came from. Know when Zilliz was founded or where it is based? Send it to us, free.