- Home
- Vector Databases
- ZeusDB Vector Database
ZeusDB Vector Database
What it is
ZeusDB Vector Database is a free, open-source vector database for AI workloads such as semantic search, retrieval-augmented generation, and recommendations. Its self-hosted plan provides a Python API and approximate nearest-neighbor search through HNSW graphs. Optional Product Quantization compresses vectors for memory efficiency. Metadata filtering is supported, along with saving and reloading indexes, metadata, and quantized vectors; hybrid search is listed as available. Package wheels cover Linux x86_64 and aarch64, macOS Apple Silicon, and Windows x86_64, with Python 3.10 through 3.14 listed. LangChain and LlamaIndex integrations are available, while Hugging Face, Anthropic, OpenAI, and Semantic Kernel are in development. An enterprise plan describes managed deployment, SSO, role-based access, audit trails, encryption, backups, restore, observability, SLAs, and priority support. The managed enterprise edition is in development. ZeusDB says it was founded and launched its first site in 2012.
For and against
For
- Free open-source self-hosted plan
- HNSW approximate nearest-neighbor search
- Optional Product Quantization
- Metadata filtering and persistence
- LangChain and LlamaIndex integrations
Against
- Managed enterprise edition is still in development
- Self-hosted deployment requires customer operations
The verdict
ZeusDB offers core vector-search functions, persistence, filtering, and Python support across several platforms. Teams needing managed enterprise controls should note that edition’s development status.
Who it suits
ZeusDB suits developers building AI search, RAG, or recommendation systems who want self-hosted vector storage. Python users on the listed operating systems can use its API and framework integrations.
Plans and prices
Open Source
Self hosted · Community supported · Python API · HNSW search
Read 8 Oct 2026 · zeusdb.com
Enterprise
Fully managed · SSO and RBAC · Audit trails and encryption · Automated backups and restore
Read 8 Oct 2026 · zeusdb.com
On the record
- Company history
- ZeusDB’s company page says it was founded and its first site launched in 2012.zeusdb.com · read 8 Oct 2026
- Compression
- Optional Product Quantization compresses vectors to improve memory efficiency.zeusdb.com · read 8 Oct 2026
- Current enterprise status
- The page says the managed enterprise edition is in development.zeusdb.com · read 8 Oct 2026
- Filtering and persistence
- The product supports metadata filtering and saving and reloading indexes, metadata, and quantized vectors.zeusdb.com · read 8 Oct 2026
- Framework integration details
- The integration documentation lists stable LangChain and LlamaIndex packages and describes vector-store features including metadata filtering and persistence.docs.zeusdb.com · read 8 Oct 2026
- Integrations
- The product page lists LangChain and LlamaIndex as available integrations; Hugging Face, Anthropic, OpenAI, and Semantic Kernel are listed as in development.zeusdb.com · read 8 Oct 2026
- Platform support
- Published package wheels are listed for Linux x86_64 and aarch64, macOS Apple Silicon, and Windows x86_64.docs.zeusdb.com · read 8 Oct 2026
- Purpose
- ZeusDB Vector Database is presented as a high-performance vector database for AI workloads, including semantic search, RAG, and recommendations.zeusdb.com · read 8 Oct 2026
- Python versions
- The package page lists support for Python 3.10 through 3.14.docs.zeusdb.com · read 8 Oct 2026
- Search
- It supports approximate nearest-neighbor search using HNSW graphs.zeusdb.com · read 8 Oct 2026
- Security and operations
- The page lists SSO, RBAC, audit trails, encryption, automated backups, restore, observability, and SLAs as enterprise features.zeusdb.com · read 8 Oct 2026
- Support
- The open-source plan is community supported, while the enterprise plan lists priority support.zeusdb.com · read 8 Oct 2026
