--- title: "airflow vs Alpaca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-airflow-vs-jeffser-alpaca" tools: ["apache-airflow", "jeffser-alpaca"] --- # airflow vs Alpaca *GraphCanon updated Jul 15, 2026* ## Verdict Pick airflow when license: airflow is Apache-2.0, Alpaca is GPL-3.0; pick Alpaca when license: Alpaca is GPL-3.0, 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. [Alpaca](https://jeffser.com/alpaca) has 1.6k stars, 144 forks, and 122 open issues, last pushed Jun 26, 2026. Figures are from public GitHub metadata via [airflow's repository](https://github.com/apache/airflow) and [Alpaca's repository](https://github.com/Jeffser/Alpaca). | | [airflow](/tools/apache-airflow.md) | [Alpaca](/tools/jeffser-alpaca.md) | | --- | --- | --- | | Tagline | Apache Airflow - A platform to programmatically author, schedule, and monitor workflows | 🦙 Local and online AI hub | | Stars | 46,124 | 1,601 | | Forks | 17,387 | 144 | | Open issues | 1,728 | 122 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | GPL-3.0 | | Categories | AI Agents, Computer Vision, Data & Retrieval | Computer Vision, Inference & Serving, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [airflow](/tools/apache-airflow.md) | [Alpaca](/tools/jeffser-alpaca.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 19d | | Open issues (now) | 1.7k | 122 | | Owner type | Organization | User | | Full report | [trust report](/tools/apache-airflow/trust.md) | [trust report](/tools/jeffser-alpaca/trust.md) | ## Choose when ### Choose airflow if… - License: airflow is Apache-2.0, Alpaca is GPL-3.0. - Tags unique to airflow: airflow, apache, apache-airflow, automation. - Also covers AI Agents, Data & Retrieval. - airflow ships Docker support for self-hosted deployment. ### Choose Alpaca if… - License: Alpaca is GPL-3.0, airflow is Apache-2.0. - Tags unique to Alpaca: adwaita, flatpak, gnome, gtk4. - Also covers Inference & Serving, Vector Databases. ## 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 Alpaca - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between airflow and Alpaca? airflow: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows. Alpaca: 🦙 Local and online AI hub. See the comparison table for live GitHub stats and shared categories. ### When should I choose airflow over Alpaca? Choose airflow over Alpaca when License: airflow is Apache-2.0, Alpaca is GPL-3.0; Tags unique to airflow: airflow, apache, apache-airflow, automation; Also covers AI Agents, Data & Retrieval; airflow ships Docker support for self-hosted deployment. ### When should I choose Alpaca over airflow? Choose Alpaca over airflow when License: Alpaca is GPL-3.0, airflow is Apache-2.0; Tags unique to Alpaca: adwaita, flatpak, gnome, gtk4; Also covers Inference & Serving, Vector Databases. ### 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 Alpaca? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is airflow or Alpaca more popular on GitHub? airflow has more GitHub stars (46,124 vs 1,601). Stars measure visibility, not whether either tool fits your constraints. ### Are airflow and Alpaca open source? Yes - both are open-source projects on GitHub (airflow: Apache-2.0, Alpaca: GPL-3.0). ### Where can I find alternatives to airflow or Alpaca? GraphCanon lists graph-backed alternatives at [airflow alternatives](/tools/apache-airflow/alternatives) and [Alpaca alternatives](/tools/jeffser-alpaca/alternatives) ([airflow markdown twin](/tools/apache-airflow/alternatives.md), [Alpaca markdown twin](/tools/jeffser-alpaca/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-jeffser-alpaca.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, airflow or Alpaca? airflow: Very active. Alpaca: 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 Alpaca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [airflow trust report](/tools/apache-airflow/trust); [Alpaca trust report](/tools/jeffser-alpaca/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/_