--- title: "evalml vs caffe" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alteryx-evalml-vs-bvlc-caffe" tools: ["alteryx-evalml", "bvlc-caffe"] --- # evalml vs caffe *GraphCanon updated Jul 11, 2026* ## Verdict Pick evalml when evalml is primarily Python; caffe is C++; pick caffe when caffe is primarily C++; evalml is Python. [evalml](https://evalml.alteryx.com) reports 849 GitHub stars, 93 forks, and 324 open issues, last pushed Jan 14, 2026. [caffe](http://caffe.berkeleyvision.org/) has 35k stars, 18k forks, and 1.2k open issues, last pushed Jul 31, 2024. Figures are from public GitHub metadata via [evalml's repository](https://github.com/alteryx/evalml) and [caffe's repository](https://github.com/BVLC/caffe). | | [evalml](/tools/alteryx-evalml.md) | [caffe](/tools/bvlc-caffe.md) | | --- | --- | --- | | Tagline | EvalML is an AutoML library written in python. | Caffe: a fast open framework for deep learning. | | Stars | 849 | 34,574 | | Forks | 93 | 18,458 | | Open issues | 324 | 1,209 | | Language | Python | C++ | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | BSD-3-Clause | Other | | Categories | Evaluation & Observability, Vector Databases | Computer Vision, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evalml](/tools/alteryx-evalml.md) | [caffe](/tools/bvlc-caffe.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 178d | 710d | | Open issues (now) | 324 | 1.2k | | Full report | [trust report](/tools/alteryx-evalml/trust.md) | [trust report](/tools/bvlc-caffe/trust.md) | ## Choose when ### Choose evalml if… - evalml is primarily Python; caffe is C++. - License: evalml is BSD-3-Clause, caffe is Other. - Tags unique to evalml: automl, data-science, feature-engineering, feature-selection. - Also covers Evaluation & Observability. ### Choose caffe if… - caffe is primarily C++; evalml is Python. - License: caffe is Other, evalml is BSD-3-Clause. - Tags unique to caffe: c++, deep-learning, vision. - Also covers Computer Vision. ## When NOT to use evalml - Last GitHub push was 178 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on evalml. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use caffe - Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. - 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 evalml and caffe? evalml: EvalML is an AutoML library written in python.. caffe: Caffe: a fast open framework for deep learning.. See the comparison table for live GitHub stats and shared categories. ### When should I choose evalml over caffe? Choose evalml over caffe when evalml is primarily Python; caffe is C++; License: evalml is BSD-3-Clause, caffe is Other; Tags unique to evalml: automl, data-science, feature-engineering, feature-selection; Also covers Evaluation & Observability. ### When should I choose caffe over evalml? Choose caffe over evalml when caffe is primarily C++; evalml is Python; License: caffe is Other, evalml is BSD-3-Clause; Tags unique to caffe: c++, deep-learning, vision; Also covers Computer Vision. ### When should I avoid evalml? Last GitHub push was 178 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on evalml. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid caffe? Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is evalml or caffe more popular on GitHub? caffe has more GitHub stars (34,574 vs 849). Stars measure visibility, not whether either tool fits your constraints. ### Are evalml and caffe open source? Yes - both are open-source projects on GitHub (evalml: BSD-3-Clause, caffe: Other). ### Where can I find alternatives to evalml or caffe? GraphCanon lists graph-backed alternatives at [evalml alternatives](/tools/alteryx-evalml/alternatives) and [caffe alternatives](/tools/bvlc-caffe/alternatives) ([evalml markdown twin](/tools/alteryx-evalml/alternatives.md), [caffe markdown twin](/tools/bvlc-caffe/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/alteryx-evalml-vs-bvlc-caffe.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, evalml or caffe? evalml: Slowing. caffe: Dormant. 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 evalml and caffe? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evalml trust report](/tools/alteryx-evalml/trust); [caffe trust report](/tools/bvlc-caffe/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=alteryx-evalml`](/api/graphcanon/graph?tool=alteryx-evalml) - 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/_