--- title: "azure-search-vector-samples vs awesome-production-machine-learning" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/azure-azure-search-vector-samples-vs-ethicalml-awesome-production-machine-learning" tools: ["azure-azure-search-vector-samples", "ethicalml-awesome-production-machine-learning"] --- # azure-search-vector-samples vs awesome-production-machine-learning *GraphCanon updated Jul 11, 2026* ## Verdict Pick azure-search-vector-samples when tags unique to azure-search-vector-samples: azure, azurecognitivesearch, embeddings, jupyter notebook; pick awesome-production-machine-learning when tags unique to awesome-production-machine-learning: awesome, awesome-list, data-mining, deep-learning. [azure-search-vector-samples](https://azure.microsoft.com/products/search) reports 909 GitHub stars, 378 forks, and 77 open issues, last pushed Feb 25, 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 [azure-search-vector-samples's repository](https://github.com/Azure/azure-search-vector-samples) and [awesome-production-machine-learning's repository](https://github.com/EthicalML/awesome-production-machine-learning). | | [azure-search-vector-samples](/tools/azure-azure-search-vector-samples.md) | [awesome-production-machine-learning](/tools/ethicalml-awesome-production-machine-learning.md) | | --- | --- | --- | | Tagline | A repository of code samples for Vector search capabilities in Azure AI Search. | A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning | | Stars | 909 | 20,719 | | Forks | 378 | 2,585 | | Open issues | 77 | 32 | | Language | Jupyter Notebook | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Vector Databases | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [azure-search-vector-samples](/tools/azure-azure-search-vector-samples.md) | [awesome-production-machine-learning](/tools/ethicalml-awesome-production-machine-learning.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 135d | 8d | | Open issues (now) | 77 | 32 | | Full report | [trust report](/tools/azure-azure-search-vector-samples/trust.md) | [trust report](/tools/ethicalml-awesome-production-machine-learning/trust.md) | ## Choose when ### Choose azure-search-vector-samples if… - Tags unique to azure-search-vector-samples: azure, azurecognitivesearch, embeddings, jupyter notebook. ### Choose awesome-production-machine-learning if… - Tags unique to awesome-production-machine-learning: awesome, awesome-list, data-mining, deep-learning. - Also covers AI Agents, LLM Frameworks. - More GitHub stars (21k vs 909) - visibility, not fit. ## When NOT to use azure-search-vector-samples - Last GitHub push was 136 days ago (slowing maintenance, Feb 25, 2026). Validate activity before betting a new project on azure-search-vector-samples. - 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 - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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 azure-search-vector-samples and awesome-production-machine-learning? azure-search-vector-samples: A repository of code samples for Vector search capabilities in Azure AI Search.. 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 azure-search-vector-samples over awesome-production-machine-learning? Choose azure-search-vector-samples over awesome-production-machine-learning when Tags unique to azure-search-vector-samples: azure, azurecognitivesearch, embeddings, jupyter notebook. ### When should I choose awesome-production-machine-learning over azure-search-vector-samples? Choose awesome-production-machine-learning over azure-search-vector-samples when Tags unique to awesome-production-machine-learning: awesome, awesome-list, data-mining, deep-learning; Also covers AI Agents, LLM Frameworks; More GitHub stars (21k vs 909) - visibility, not fit. ### When should I avoid azure-search-vector-samples? Last GitHub push was 136 days ago (slowing maintenance, Feb 25, 2026). Validate activity before betting a new project on azure-search-vector-samples. 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? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is azure-search-vector-samples or awesome-production-machine-learning more popular on GitHub? awesome-production-machine-learning has more GitHub stars (20,719 vs 909). Stars measure visibility, not whether either tool fits your constraints. ### Are azure-search-vector-samples and awesome-production-machine-learning open source? Yes - both are open-source projects on GitHub (azure-search-vector-samples: MIT, awesome-production-machine-learning: MIT). ### Where can I find alternatives to azure-search-vector-samples or awesome-production-machine-learning? GraphCanon lists graph-backed alternatives at [azure-search-vector-samples alternatives](/tools/azure-azure-search-vector-samples/alternatives) and [awesome-production-machine-learning alternatives](/tools/ethicalml-awesome-production-machine-learning/alternatives) ([azure-search-vector-samples markdown twin](/tools/azure-azure-search-vector-samples/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/azure-azure-search-vector-samples-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, azure-search-vector-samples or awesome-production-machine-learning? azure-search-vector-samples: Slowing. 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 azure-search-vector-samples and awesome-production-machine-learning? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [azure-search-vector-samples trust report](/tools/azure-azure-search-vector-samples/trust); [awesome-production-machine-learning trust report](/tools/ethicalml-awesome-production-machine-learning/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=azure-azure-search-vector-samples`](/api/graphcanon/graph?tool=azure-azure-search-vector-samples) - 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/_