--- title: "awesome-vector-search vs chromem-go" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/currentslab-awesome-vector-search-vs-philippgille-chromem-go" tools: ["currentslab-awesome-vector-search", "philippgille-chromem-go"] --- # awesome-vector-search vs chromem-go *GraphCanon updated Aug 21, 2026* ## Verdict Pick awesome-vector-search if curated collection of vector search-related resources including libraries, services, and research papers; pick chromem-go if chromem-go is an embeddable vector database for Go that provides a Chroma-like interface with no third-party dependencies, suitable for applications needing in-memory persistence and cosine similarity search capabilities. [awesome-vector-search](https://github.com/currentslab/awesome-vector-search) reports 1.6k GitHub stars, 123 forks, and 14 open issues, last pushed Jul 6, 2026. [chromem-go](https://github.com/philippgille/chromem-go) has 1.0k stars, 75 forks, and 18 open issues, last pushed May 17, 2026. Figures are from public GitHub metadata via [awesome-vector-search's repository](https://github.com/currentslab/awesome-vector-search) and [chromem-go's repository](https://github.com/philippgille/chromem-go). | | [awesome-vector-search](/tools/currentslab-awesome-vector-search.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Tagline | Collections of vector search related libraries, service and research papers | Embeddable vector database for Go with Chroma-like interface. | | Stars | 1,576 | 1,047 | | Forks | 123 | 75 | | Open issues | 14 | 18 | | Language | - | Go | | Adopt for | Curated collection of vector search-related resources including libraries, services, and research papers. | Chromem-go is an embeddable vector database for Go that provides a Chroma-like interface with no third-party dependencies, suitable for applications needing in-memory persistence and cosine similarity search capabilities | | Persona | - | - | | Runtime | - | - | | License | MIT | MPL-2.0 | | Categories | Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-vector-search](/tools/currentslab-awesome-vector-search.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 17d | 96d | | Open issues (now) | 14 | 18 | | Stars delta | Unknown | +14 (30d) | | Open issues delta | Unknown | +1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/currentslab-awesome-vector-search/trust.md) | [trust report](/tools/philippgille-chromem-go/trust.md) | ## Decision facts: awesome-vector-search - **Adopt for:** Curated collection of vector search-related resources including libraries, services, and research papers. ## Decision facts: chromem-go - **Requirements:** Min 0.5 GB RAM - **Adopt for:** Chromem-go is an embeddable vector database for Go that provides a Chroma-like interface with no third-party dependencies, suitable for applications needing in-memory persistence and cosine similarity search capabilities ## Choose when ### Choose awesome-vector-search if… - License: awesome-vector-search is MIT, chromem-go is MPL-2.0. - Tags unique to awesome-vector-search: awesome, awesome-list, knn-search, machine-learning. - You need a comprehensive overview of vector search technology. ### Choose chromem-go if… - License: chromem-go is MPL-2.0, awesome-vector-search is MIT. - Requirements: Min 0.5 GB RAM. - Tags unique to chromem-go: chroma, cosine-similarity, embeddings, in-memory. - If you are building applications in Go and require an in-memory vector database without additional third-party libraries. ## When NOT to use awesome-vector-search - Require real-time vector search service implementation details outside listed libraries. - Seeking detailed code tutorials rather than a list of resources. ## When NOT to use chromem-go - Avoid Chromem-go if you seek a traditional, disk-based persistence model as it primarily supports in-memory operations with optional persistence options. - Chromem-go is not the best choice if your application requires heavy concurrent load and large-scale data handling which might surpass the in-memory capability limits of this library. ## Common questions ### What is the difference between awesome-vector-search and chromem-go? awesome-vector-search: Collections of vector search related libraries, service and research papers. chromem-go: Embeddable vector database for Go with Chroma-like interface.. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-vector-search over chromem-go? Choose awesome-vector-search over chromem-go when License: awesome-vector-search is MIT, chromem-go is MPL-2.0; Tags unique to awesome-vector-search: awesome, awesome-list, knn-search, machine-learning; You need a comprehensive overview of vector search technology. ### When should I choose chromem-go over awesome-vector-search? Choose chromem-go over awesome-vector-search when License: chromem-go is MPL-2.0, awesome-vector-search is MIT; Requirements: Min 0.5 GB RAM; Tags unique to chromem-go: chroma, cosine-similarity, embeddings, in-memory; If you are building applications in Go and require an in-memory vector database without additional third-party libraries. ### When should I avoid awesome-vector-search? Require real-time vector search service implementation details outside listed libraries. Seeking detailed code tutorials rather than a list of resources. ### When should I avoid chromem-go? Avoid Chromem-go if you seek a traditional, disk-based persistence model as it primarily supports in-memory operations with optional persistence options. Chromem-go is not the best choice if your application requires heavy concurrent load and large-scale data handling which might surpass the in-memory capability limits of this library. ### Is awesome-vector-search or chromem-go more popular on GitHub? awesome-vector-search has more GitHub stars (1,576 vs 1,047). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-vector-search and chromem-go open source? Yes - both are open-source projects on GitHub (awesome-vector-search: MIT, chromem-go: MPL-2.0). ### Where can I find alternatives to awesome-vector-search or chromem-go? GraphCanon lists graph-backed alternatives at [awesome-vector-search alternatives](/tools/currentslab-awesome-vector-search/alternatives) and [chromem-go alternatives](/tools/philippgille-chromem-go/alternatives) ([awesome-vector-search markdown twin](/tools/currentslab-awesome-vector-search/alternatives.md), [chromem-go markdown twin](/tools/philippgille-chromem-go/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/currentslab-awesome-vector-search-vs-philippgille-chromem-go.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-vector-search or chromem-go? awesome-vector-search: Active. chromem-go: Slowing. 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 awesome-vector-search and chromem-go? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-vector-search trust report](/tools/currentslab-awesome-vector-search/trust); [chromem-go trust report](/tools/philippgille-chromem-go/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=currentslab-awesome-vector-search`](/api/graphcanon/graph?tool=currentslab-awesome-vector-search) - 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/_