--- title: "obsidian-smart-connections vs awesome-production-machine-learning" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/brianpetro-obsidian-smart-connections-vs-ethicalml-awesome-production-machine-learning" tools: ["brianpetro-obsidian-smart-connections", "ethicalml-awesome-production-machine-learning"] --- # obsidian-smart-connections vs awesome-production-machine-learning *GraphCanon updated Jul 12, 2026* ## Verdict Pick obsidian-smart-connections when license: obsidian-smart-connections is Other, awesome-production-machine-learning is MIT; pick awesome-production-machine-learning when license: awesome-production-machine-learning is MIT, obsidian-smart-connections is Other. [obsidian-smart-connections](https://smartconnections.app) reports 5.3k GitHub stars, 327 forks, and 484 open issues, last pushed Jul 4, 2026. [awesome-production-machine-learning](https://ethicalml.github.io/awesome-production-machine-learning) has 21k stars, 2.6k forks, and 32 open issues, last pushed Jul 3, 2026. Figures are from public GitHub metadata via [obsidian-smart-connections's repository](https://github.com/brianpetro/obsidian-smart-connections) and [awesome-production-machine-learning's repository](https://github.com/EthicalML/awesome-production-machine-learning). | | [obsidian-smart-connections](/tools/brianpetro-obsidian-smart-connections.md) | [awesome-production-machine-learning](/tools/ethicalml-awesome-production-machine-learning.md) | | --- | --- | --- | | Tagline | Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key. | A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning | | Stars | 5,262 | 20,719 | | Forks | 327 | 2,585 | | Open issues | 484 | 32 | | Language | JavaScript | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Vector Databases | LLM Frameworks, AI Agents, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [obsidian-smart-connections](/tools/brianpetro-obsidian-smart-connections.md) | [awesome-production-machine-learning](/tools/ethicalml-awesome-production-machine-learning.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 6d | 8d | | Open issues (now) | 484 | 32 | | Owner type | User | Organization | | Full report | [trust report](/tools/brianpetro-obsidian-smart-connections/trust.md) | [trust report](/tools/ethicalml-awesome-production-machine-learning/trust.md) | ## Choose when ### Choose obsidian-smart-connections if… - License: obsidian-smart-connections is Other, awesome-production-machine-learning is MIT. - Tags unique to obsidian-smart-connections: embeddings, related-items, obsidian, gemini. - More recently updated (last pushed Jul 4, 2026). ### Choose awesome-production-machine-learning if… - License: awesome-production-machine-learning is MIT, obsidian-smart-connections is Other. - Tags unique to awesome-production-machine-learning: awesome, deep-learning, data-mining, large-scale-ml. - Also covers LLM Frameworks, AI Agents. ## When NOT to use obsidian-smart-connections - 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 awesome-production-machine-learning - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - 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 obsidian-smart-connections and awesome-production-machine-learning? obsidian-smart-connections: Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.. awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning. See the comparison table for live GitHub stats and shared categories. ### When should I choose obsidian-smart-connections over awesome-production-machine-learning? Choose obsidian-smart-connections over awesome-production-machine-learning when License: obsidian-smart-connections is Other, awesome-production-machine-learning is MIT; Tags unique to obsidian-smart-connections: embeddings, related-items, obsidian, gemini; More recently updated (last pushed Jul 4, 2026). ### When should I choose awesome-production-machine-learning over obsidian-smart-connections? Choose awesome-production-machine-learning over obsidian-smart-connections when License: awesome-production-machine-learning is MIT, obsidian-smart-connections is Other; Tags unique to awesome-production-machine-learning: awesome, deep-learning, data-mining, large-scale-ml; Also covers LLM Frameworks, AI Agents. ### When should I avoid obsidian-smart-connections? 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 awesome-production-machine-learning? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is obsidian-smart-connections or awesome-production-machine-learning more popular on GitHub? awesome-production-machine-learning has more GitHub stars (20,719 vs 5,262). Stars measure visibility, not whether either tool fits your constraints. ### Are obsidian-smart-connections and awesome-production-machine-learning open source? Yes - both are open-source projects on GitHub (obsidian-smart-connections: Other, awesome-production-machine-learning: MIT). ### Where can I find alternatives to obsidian-smart-connections or awesome-production-machine-learning? GraphCanon lists graph-backed alternatives at [obsidian-smart-connections alternatives](/tools/brianpetro-obsidian-smart-connections/alternatives) and [awesome-production-machine-learning alternatives](/tools/ethicalml-awesome-production-machine-learning/alternatives) ([obsidian-smart-connections markdown twin](/tools/brianpetro-obsidian-smart-connections/alternatives.md), [awesome-production-machine-learning markdown twin](/tools/ethicalml-awesome-production-machine-learning/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/brianpetro-obsidian-smart-connections-vs-ethicalml-awesome-production-machine-learning.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, obsidian-smart-connections or awesome-production-machine-learning? obsidian-smart-connections: Very active. awesome-production-machine-learning: 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 obsidian-smart-connections and awesome-production-machine-learning? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [obsidian-smart-connections trust report](/tools/brianpetro-obsidian-smart-connections/trust); [awesome-production-machine-learning trust report](/tools/ethicalml-awesome-production-machine-learning/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=brianpetro-obsidian-smart-connections`](/api/graphcanon/graph?tool=brianpetro-obsidian-smart-connections) - 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/_