--- title: "infinity vs autoflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/infiniflow-infinity-vs-pingcap-autoflow" tools: ["infiniflow-infinity", "pingcap-autoflow"] --- # infinity vs autoflow *GraphCanon updated Aug 21, 2026* ## Verdict Pick infinity if designed for high-speed hybrid searches in LLM applications, infinity supports dense vector, sparse vector, tensor, and full-text data types; pick autoflow if pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. [infinity](https://infiniflow.org) reports 4.7k GitHub stars, 437 forks, and 64 open issues, last pushed Aug 17, 2026. [autoflow](https://tidb.ai) has 3.0k stars, 194 forks, and 74 open issues, last pushed Apr 27, 2026. Figures are from public GitHub metadata via [infinity's repository](https://github.com/infiniflow/infinity) and [autoflow's repository](https://github.com/pingcap/autoflow). | | [infinity](/tools/infiniflow-infinity.md) | [autoflow](/tools/pingcap-autoflow.md) | | --- | --- | --- | | Tagline | AI-native database for LLM applications offering fast hybrid search capabilities. | Graph RAG based conversational knowledge base tool using TiDB Serverless Vector Storage | | Stars | 4,675 | 2,971 | | Forks | 437 | 194 | | Open issues | 64 | 74 | | Language | C++ | TypeScript | | Adopt for | Designed for high-speed hybrid searches in LLM applications, infinity supports dense vector, sparse vector, tensor, and full-text data types. | pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [infinity](/tools/infiniflow-infinity.md) | [autoflow](/tools/pingcap-autoflow.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 3d | 115d | | Open issues (now) | 64 | 74 | | Stars delta | +51 (30d) | +15 (30d) | | Open issues delta | -2 (30d) | -1 (30d) | | Full report | [trust report](/tools/infiniflow-infinity/trust.md) | [trust report](/tools/pingcap-autoflow/trust.md) | **Typed relationship:** infinity _(integrates with)_ autoflow Autoflow uses TiDB Vector Storage which can integrate well with infinity for hybrid search capabilities, as both deal with vector and knowledge graph integration. ## Decision facts: infinity - **Adopt for:** Designed for high-speed hybrid searches in LLM applications, infinity supports dense vector, sparse vector, tensor, and full-text data types. ## Decision facts: autoflow - **Adopt for:** pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. ## Choose when ### Choose infinity if… - infinity is primarily C++; autoflow is TypeScript. - Autoflow uses TiDB Vector Storage which can integrate well with infinity for hybrid search capabilities, as both deal with vector and knowledge graph integration. - Tags unique to infinity: ai-native, approximate-nearest-neighbor-search, bm25, cpp20. - When your application requires rapid hybrid search capabilities across multiple data types including tensors and full texts. ### Choose autoflow if… - autoflow is primarily TypeScript; infinity is C++. - Autoflow uses TiDB Vector Storage which can integrate well with infinity for hybrid search capabilities, as both deal with vector and knowledge graph integration. - Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph. - autoflow ships Docker support for self-hosted deployment. - - When you need to create a conversational interface that can leverage both graph-based data structures and retrieval-augmented generation techniques for context-aware responses. ## When NOT to use infinity - If your project does not benefit from fast hybrid search features or if you prefer not to use an AI-native database solution. - When support for only dense vectors is sufficient, and the added complexity of supporting tensors and full texts is unnecessary. ## When NOT to use autoflow - - When your application does not require a conversational knowledge base or cannot benefit from retrieval-augmented generation (RAG) techniques. - - If you are aiming for broad compatibility across different SQL-based databases, as autoflow specifically integrates with TiDB and might offer less flexibility when compared to tools that support a ## Common questions ### What is the difference between infinity and autoflow? infinity: AI-native database for LLM applications offering fast hybrid search capabilities.. autoflow: Graph RAG based conversational knowledge base tool using TiDB Serverless Vector Storage. See the comparison table for live GitHub stats and shared categories. ### When should I choose infinity over autoflow? Choose infinity over autoflow when infinity is primarily C++; autoflow is TypeScript; Autoflow uses TiDB Vector Storage which can integrate well with infinity for hybrid search capabilities, as both deal with vector and knowledge graph integration; Tags unique to infinity: ai-native, approximate-nearest-neighbor-search, bm25, cpp20; When your application requires rapid hybrid search capabilities across multiple data types including tensors and full texts. ### When should I choose autoflow over infinity? Choose autoflow over infinity when autoflow is primarily TypeScript; infinity is C++; Autoflow uses TiDB Vector Storage which can integrate well with infinity for hybrid search capabilities, as both deal with vector and knowledge graph integration; Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph; autoflow ships Docker support for self-hosted deployment; - When you need to create a conversational interface that can leverage both graph-based data structures and retrieval-augmented generation techniques for context-aware responses. ### When should I avoid infinity? If your project does not benefit from fast hybrid search features or if you prefer not to use an AI-native database solution. When support for only dense vectors is sufficient, and the added complexity of supporting tensors and full texts is unnecessary. ### When should I avoid autoflow? - When your application does not require a conversational knowledge base or cannot benefit from retrieval-augmented generation (RAG) techniques. - If you are aiming for broad compatibility across different SQL-based databases, as autoflow specifically integrates with TiDB and might offer less flexibility when compared to tools that support a ### Is infinity or autoflow more popular on GitHub? infinity has more GitHub stars (4,675 vs 2,971). Stars measure visibility, not whether either tool fits your constraints. ### Are infinity and autoflow open source? Yes - both are open-source projects on GitHub (infinity: Apache-2.0, autoflow: Apache-2.0). ### Where can I find alternatives to infinity or autoflow? GraphCanon lists graph-backed alternatives at [infinity alternatives](/tools/infiniflow-infinity/alternatives) and [autoflow alternatives](/tools/pingcap-autoflow/alternatives) ([infinity markdown twin](/tools/infiniflow-infinity/alternatives.md), [autoflow markdown twin](/tools/pingcap-autoflow/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/infiniflow-infinity-vs-pingcap-autoflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, infinity or autoflow? infinity: Very active. autoflow: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for infinity and autoflow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [infinity trust report](/tools/infiniflow-infinity/trust); [autoflow trust report](/tools/pingcap-autoflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=infiniflow-infinity`](/api/graphcanon/graph?tool=infiniflow-infinity) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_