Compare Milvus and Supabase side by side. Both are tools in the Vector Databases category.
Updated February 28, 2026
Choose Milvus if extreme scalability handling billions of vectors in distributed environments.
| Category | Vector Databases | Vector Databases |
| Pricing | Open Source | freemium |
| Best For | Organizations that need vector search at billion-scale with high throughput | Full-stack developers building AI apps |
| Website | milvus.io | supabase.com |
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Key criteria to evaluate when comparing Vector Databases solutions:
Milvus is an open-source vector database built for scalable similarity search, capable of handling billions of vectors in distributed environments. Created by Zilliz, a company founded in 2017 by Charles Xie (former founding engineer of Oracle 12c cloud database), Milvus has become one of the most widely deployed vector databases with over 30,000 GitHub stars.
The database supports multiple index types including IVF, HNSW, and DiskANN, with GPU-accelerated search and hybrid search combining dense and sparse vectors in a single query. Milvus runs on Kubernetes for production deployments and is governed under the LF AI & Data Foundation. Zilliz Cloud offers a fully managed version with automatic scaling, starting with a free tier and usage-based pricing from $4 per million vector compute units.
Zilliz has raised approximately $113-132 million in funding, with a $60 million Series B extension in August 2022 led by Prosperity7 Ventures (Aramco). The company is headquartered in San Francisco with roughly 140 employees. Zilliz was named "Highest Performer" and "Easiest to Use" in G2's Summer 2025 Vector Database Grid Report.
The #1 platform for pgvector. Open-source Firebase alternative with built-in vector search via Postgres.
Purpose-built databases for storing, indexing, and querying high-dimensional vector embeddings used in semantic search, RAG, and recommendation systems.
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