infinity
Infinity is an open-source database designed specifically for AI and LLM applications, supporting fast searches across vectors (dense and sparse), full-text, and structured data. It combines multiple search capabilities—hybrid search, filtering, and reranking—in a single system optimized for RAG and recommendation use cases.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | infiniflow/infinity |
| Owner | infiniflow |
| Primary language | C++ |
| License | Apache-2.0 — OSI-approved |
| Stars | 4.6k |
| Forks | 430 |
| Open issues | 65 |
| Latest release | v0.7.0 (2026-05-15) |
| Last updated | 2026-06-29 |
| Source | https://github.com/infiniflow/infinity |
What infinity is
C++20 implementation providing sub-millisecond query latency (0.1ms on million-scale vectors) and 15K+ QPS via HNSW-based approximate nearest neighbor search, BM25 full-text indexing, and tensor support. Single-binary deployment with Python SDK and HTTP API; requires x86_64 AVX2, glibc 2.17+, and Python 3.11+.
Get the infinity source
Clone the repository and explore it locally.
git clone https://github.com/infiniflow/infinity.gitcd infinity# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Requires Python 3.11+ and x86_64 AVX2 CPU; verify hardware/OS compatibility before deployment (Linux glibc 2.17+, macOS x86_64, or Windows via WSL2).
- Single-binary design with no external dependencies simplifies deployment, but embedding in Python or running as separate client/server process affects architecture decisions.
- Hybrid search setup requires tuning query composition (dense, sparse, full-text, filters, reranker weights) for your specific use case; benchmark with real data.
- SDK is Python-first; HTTP API available for language-agnostic access but may lack feature parity compared to Python SDK.
- Default Docker deployment uses `/var/infinity` volume; plan persistent storage, ulimit configuration (500000 file descriptors), and resource allocation.
When to avoid it — and what to weigh
- Non-x86_64 or Older CPU Architectures — Requires x86_64 with AVX2 support; not suitable for ARM64, older x86, or systems without AVX2 acceleration.
- Windows Without WSL/WSL2 — Native Windows support is not available; Windows 10+ requires WSL or WSL2, which adds operational complexity.
- Transactional ACID Compliance Critical — Purpose-built as a search/analytics database; if ACID transactions and strong consistency guarantees are primary requirements, traditional RDBMS may be better suited.
- Early-Stage Production with Minimal Risk Tolerance — Latest release is v0.7.0 (May 2026); project is actively developed but version numbering suggests pre-1.0 maturity. Requires careful evaluation for mission-critical systems.
License & commercial use
Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved open-source license.
Apache-2.0 permits commercial use, modification, and distribution with attribution and no warranty. No proprietary or commercial restrictions are evident from the license. However, review terms of service and any commercial support offerings from infiniflow separately to confirm no additional restrictions apply.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
Not clearly stated in provided data. Evaluate: network isolation (default `--network=host` may expose services), authentication/authorization mechanisms (unknown from docs excerpt), encryption at rest/in transit, and input validation for query injection. No security audit or CVE history provided. Recommend independent security review before production deployment.
Alternatives to consider
Milvus
Another open-source vector database with HNSW support and distributed scaling; more mature (v2.0+) but less integrated full-text search.
Weaviate
GraphQL-based vector database with hybrid search and multimodal support; more established enterprise adoption but heavier operational footprint.
Pinecone / Qdrant
Cloud-native vector databases with strong reranking and filtering; Qdrant offers self-hosted option. Trade deployment simplicity for managed service or higher infrastructure complexity.
Build on infinity with DEV.co software developers
Infinity offers fast hybrid search for embeddings and full-text. Verify x86_64 AVX2 support and test with your data before production. Contact our team to explore integration or deployment strategy.
Talk to DEV.coRelated on DEV.co
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infinity FAQ
Does Infinity support distributed/clustered deployment?
What embedding models does Infinity integrate with?
Is there a managed/cloud version of Infinity?
What are the performance guarantees (SLA)?
Software development & web development with DEV.co
Need help beyond evaluating infinity? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and vector databases integrations — and maintain them long-term.
Ready to Deploy AI-Native Search?
Infinity offers fast hybrid search for embeddings and full-text. Verify x86_64 AVX2 support and test with your data before production. Contact our team to explore integration or deployment strategy.