--- title: "hora vs chromem-go" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hora-search-hora-vs-philippgille-chromem-go" tools: ["hora-search-hora", "philippgille-chromem-go"] --- # hora vs chromem-go *GraphCanon updated Aug 21, 2026* ## Verdict Pick hora if hora is a Rust-based library for high-performance approximate nearest neighbor search algorithms critical in applications such as image and recommender systems where speed and efficiency are paramount; 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. [hora](http://horasearch.com/) reports 2.7k GitHub stars, 78 forks, and 26 open issues, last pushed Feb 17, 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 [hora's repository](https://github.com/hora-search/hora) and [chromem-go's repository](https://github.com/philippgille/chromem-go). | | [hora](/tools/hora-search-hora.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Tagline | efficient approximate nearest neighbor search algorithm collections library written in Rust | Embeddable vector database for Go with Chroma-like interface. | | Stars | 2,663 | 1,047 | | Forks | 78 | 75 | | Open issues | 26 | 18 | | Language | Rust | Go | | Adopt for | Hora is a Rust-based library for high-performance approximate nearest neighbor search algorithms critical in applications such as image and recommender systems where speed and efficiency are paramount. | 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 | Apache-2.0 | MPL-2.0 | | Categories | Data & Retrieval, Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hora](/tools/hora-search-hora.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Days since push | 155d | 96d | | Open issues (now) | 26 | 18 | | Stars delta | Unknown | +14 (30d) | | Open issues delta | Unknown | +1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/hora-search-hora/trust.md) | [trust report](/tools/philippgille-chromem-go/trust.md) | ## Decision facts: hora - **Adopt for:** Hora is a Rust-based library for high-performance approximate nearest neighbor search algorithms critical in applications such as image and recommender systems where speed and efficiency are paramount. ## 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 hora if… - hora is primarily Rust; chromem-go is Go. - License: hora is Apache-2.0, chromem-go is MPL-2.0. - Tags unique to hora: algorithm, approximate-nearest-neighbor-search, artificial-intelligence, data-structures. - Also covers Data & Retrieval. - When you require a high-speed library written in Rust to implement an efficient similarity-search solution ### Choose chromem-go if… - chromem-go is primarily Go; hora is Rust. - License: chromem-go is MPL-2.0, hora is Apache-2.0. - 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 hora - If your project is restricted to languages other than Rust and you cannot work with Rust bindings or require a more general-purpose vector database library - When exact nearest neighbor search accuracy is preferred over the speed provided by approximate algorithms, as Hora specializes in sacrificing minimal precision for significant performance gains ## 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 hora and chromem-go? hora: efficient approximate nearest neighbor search algorithm collections library written in Rust. 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 hora over chromem-go? Choose hora over chromem-go when hora is primarily Rust; chromem-go is Go; License: hora is Apache-2.0, chromem-go is MPL-2.0; Tags unique to hora: algorithm, approximate-nearest-neighbor-search, artificial-intelligence, data-structures; Also covers Data & Retrieval; When you require a high-speed library written in Rust to implement an efficient similarity-search solution. ### When should I choose chromem-go over hora? Choose chromem-go over hora when chromem-go is primarily Go; hora is Rust; License: chromem-go is MPL-2.0, hora is Apache-2.0; 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 hora? If your project is restricted to languages other than Rust and you cannot work with Rust bindings or require a more general-purpose vector database library When exact nearest neighbor search accuracy is preferred over the speed provided by approximate algorithms, as Hora specializes in sacrificing minimal precision for significant performance gains ### 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 hora or chromem-go more popular on GitHub? hora has more GitHub stars (2,663 vs 1,047). Stars measure visibility, not whether either tool fits your constraints. ### Are hora and chromem-go open source? Yes - both are open-source projects on GitHub (hora: Apache-2.0, chromem-go: MPL-2.0). ### Where can I find alternatives to hora or chromem-go? GraphCanon lists graph-backed alternatives at [hora alternatives](/tools/hora-search-hora/alternatives) and [chromem-go alternatives](/tools/philippgille-chromem-go/alternatives) ([hora markdown twin](/tools/hora-search-hora/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/hora-search-hora-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, hora or chromem-go? hora: Slowing. 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 hora and chromem-go? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hora trust report](/tools/hora-search-hora/trust); [chromem-go trust report](/tools/philippgille-chromem-go/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hora-search-hora`](/api/graphcanon/graph?tool=hora-search-hora) - 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/_