--- title: "fastembed-rs vs chromem-go" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/anush008-fastembed-rs-vs-philippgille-chromem-go" tools: ["anush008-fastembed-rs", "philippgille-chromem-go"] --- # fastembed-rs vs chromem-go *GraphCanon updated Aug 21, 2026* ## Verdict Pick fastembed-rs if fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes; 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. [fastembed-rs](https://docs.rs/fastembed) reports 972 GitHub stars, 134 forks, and 3 open issues, last pushed Jul 15, 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 [fastembed-rs's repository](https://github.com/Anush008/fastembed-rs) and [chromem-go's repository](https://github.com/philippgille/chromem-go). | | [fastembed-rs](/tools/anush008-fastembed-rs.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Tagline | Rust library for generating vector embeddings and reranking locally. | Embeddable vector database for Go with Chroma-like interface. | | Stars | 972 | 1,047 | | Forks | 134 | 75 | | Open issues | 3 | 18 | | Language | Rust | Go | | Adopt for | fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes. | 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._ | | [fastembed-rs](/tools/anush008-fastembed-rs.md) | [chromem-go](/tools/philippgille-chromem-go.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 8d | 96d | | Open issues (now) | 3 | 18 | | Stars delta | Unknown | +14 (30d) | | Open issues delta | Unknown | +1 (30d) | | Full report | [trust report](/tools/anush008-fastembed-rs/trust.md) | [trust report](/tools/philippgille-chromem-go/trust.md) | ## Decision facts: fastembed-rs - **Adopt for:** fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes. ## 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 fastembed-rs if… - fastembed-rs is primarily Rust; chromem-go is Go. - License: fastembed-rs is Apache-2.0, chromem-go is MPL-2.0. - Tags unique to fastembed-rs: fastembed, rag, reranker, reranking. - Also covers Data & Retrieval. - When you seek high-performance embedding generation within an application written in Rust. ### Choose chromem-go if… - chromem-go is primarily Go; fastembed-rs is Rust. - License: chromem-go is MPL-2.0, fastembed-rs is Apache-2.0. - Requirements: Min 0.5 GB RAM. - Tags unique to chromem-go: chroma, cosine-similarity, in-memory, llms. - If you are building applications in Go and require an in-memory vector database without additional third-party libraries. ## When NOT to use fastembed-rs - Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages. - Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing. ## 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 fastembed-rs and chromem-go? fastembed-rs: Rust library for generating vector embeddings and reranking locally.. 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 fastembed-rs over chromem-go? Choose fastembed-rs over chromem-go when fastembed-rs is primarily Rust; chromem-go is Go; License: fastembed-rs is Apache-2.0, chromem-go is MPL-2.0; Tags unique to fastembed-rs: fastembed, rag, reranker, reranking; Also covers Data & Retrieval; When you seek high-performance embedding generation within an application written in Rust. ### When should I choose chromem-go over fastembed-rs? Choose chromem-go over fastembed-rs when chromem-go is primarily Go; fastembed-rs is Rust; License: chromem-go is MPL-2.0, fastembed-rs is Apache-2.0; Requirements: Min 0.5 GB RAM; Tags unique to chromem-go: chroma, cosine-similarity, in-memory, llms; If you are building applications in Go and require an in-memory vector database without additional third-party libraries. ### When should I avoid fastembed-rs? Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages. Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing. ### 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 fastembed-rs or chromem-go more popular on GitHub? chromem-go has more GitHub stars (1,047 vs 972). Stars measure visibility, not whether either tool fits your constraints. ### Are fastembed-rs and chromem-go open source? Yes - both are open-source projects on GitHub (fastembed-rs: Apache-2.0, chromem-go: MPL-2.0). ### Where can I find alternatives to fastembed-rs or chromem-go? GraphCanon lists graph-backed alternatives at [fastembed-rs alternatives](/tools/anush008-fastembed-rs/alternatives) and [chromem-go alternatives](/tools/philippgille-chromem-go/alternatives) ([fastembed-rs markdown twin](/tools/anush008-fastembed-rs/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/anush008-fastembed-rs-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, fastembed-rs or chromem-go? fastembed-rs: 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 fastembed-rs and chromem-go? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [fastembed-rs trust report](/tools/anush008-fastembed-rs/trust); [chromem-go trust report](/tools/philippgille-chromem-go/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=anush008-fastembed-rs`](/api/graphcanon/graph?tool=anush008-fastembed-rs) - 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/_