--- title: "airflow vs quant-mind" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-airflow-vs-llmquant-quant-mind" tools: ["apache-airflow", "llmquant-quant-mind"] --- # airflow vs quant-mind *GraphCanon updated Jul 15, 2026* ## Verdict Pick airflow when license: airflow is Apache-2.0, quant-mind is MIT; pick quant-mind when license: quant-mind is MIT, airflow is Apache-2.0. [airflow](https://airflow.apache.org/) reports 46k GitHub stars, 17k forks, and 1.7k open issues, last pushed Jul 15, 2026. [quant-mind](http://llmquantdata.com/) has 2.0k stars, 345 forks, and 32 open issues, last pushed Jul 15, 2026. Figures are from public GitHub metadata via [airflow's repository](https://github.com/apache/airflow) and [quant-mind's repository](https://github.com/LLMQuant/quant-mind). | | [airflow](/tools/apache-airflow.md) | [quant-mind](/tools/llmquant-quant-mind.md) | | --- | --- | --- | | Tagline | Apache Airflow - A platform to programmatically author, schedule, and monitor workflows | QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance. | | Stars | 46,124 | 2,006 | | Forks | 17,387 | 345 | | Open issues | 1,728 | 32 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Computer Vision, Data & Retrieval | Data & Retrieval, Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [airflow](/tools/apache-airflow.md) | [quant-mind](/tools/llmquant-quant-mind.md) | | --- | --- | --- | | Open issues (now) | 1.7k | 32 | | Full report | [trust report](/tools/apache-airflow/trust.md) | [trust report](/tools/llmquant-quant-mind/trust.md) | ## Shared compatibility - **Python**: [airflow](/tools/apache-airflow.md) - Python runtime; [quant-mind](/tools/llmquant-quant-mind.md) - Python runtime ## Choose when ### Choose airflow if… - License: airflow is Apache-2.0, quant-mind is MIT. - Tags unique to airflow: airflow, apache, apache-airflow, automation. - Also covers AI Agents, Computer Vision. - airflow ships Docker support for self-hosted deployment. ### Choose quant-mind if… - License: quant-mind is MIT, airflow is Apache-2.0. - Tags unique to quant-mind: data, knowledge, llm, pipeline. - Also covers Evaluation & Observability, LLM Frameworks. ## When NOT to use airflow - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ## When NOT to use quant-mind - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between airflow and quant-mind? airflow: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows. quant-mind: QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.. See the comparison table for live GitHub stats and shared categories. ### When should I choose airflow over quant-mind? Choose airflow over quant-mind when License: airflow is Apache-2.0, quant-mind is MIT; Tags unique to airflow: airflow, apache, apache-airflow, automation; Also covers AI Agents, Computer Vision; airflow ships Docker support for self-hosted deployment. ### When should I choose quant-mind over airflow? Choose quant-mind over airflow when License: quant-mind is MIT, airflow is Apache-2.0; Tags unique to quant-mind: data, knowledge, llm, pipeline; Also covers Evaluation & Observability, LLM Frameworks. ### When should I avoid airflow? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ### When should I avoid quant-mind? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is airflow or quant-mind more popular on GitHub? airflow has more GitHub stars (46,124 vs 2,006). Stars measure visibility, not whether either tool fits your constraints. ### Are airflow and quant-mind open source? Yes - both are open-source projects on GitHub (airflow: Apache-2.0, quant-mind: MIT). ### Where can I find alternatives to airflow or quant-mind? GraphCanon lists graph-backed alternatives at [airflow alternatives](/tools/apache-airflow/alternatives) and [quant-mind alternatives](/tools/llmquant-quant-mind/alternatives) ([airflow markdown twin](/tools/apache-airflow/alternatives.md), [quant-mind markdown twin](/tools/llmquant-quant-mind/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/apache-airflow-vs-llmquant-quant-mind.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, airflow or quant-mind? airflow: Very active. quant-mind: Very active. 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 airflow and quant-mind? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [airflow trust report](/tools/apache-airflow/trust); [quant-mind trust report](/tools/llmquant-quant-mind/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apache-airflow`](/api/graphcanon/graph?tool=apache-airflow) - 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/_