--- title: "NumKong vs meilisearch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ashvardanian-numkong-vs-meilisearch-meilisearch" tools: ["ashvardanian-numkong", "meilisearch-meilisearch"] --- # NumKong vs meilisearch *GraphCanon updated Jul 11, 2026* ## Verdict Pick NumKong when numKong is primarily C; meilisearch is Rust; pick meilisearch when meilisearch is primarily Rust; NumKong is C. [NumKong](https://ashvardanian.com/posts/numkong) reports 1.8k GitHub stars, 124 forks, and 30 open issues, last pushed Jul 9, 2026. [meilisearch](https://www.meilisearch.com) has 58k stars, 2.6k forks, and 310 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [NumKong's repository](https://github.com/ashvardanian/NumKong) and [meilisearch's repository](https://github.com/meilisearch/meilisearch). | | [NumKong](/tools/ashvardanian-numkong.md) | [meilisearch](/tools/meilisearch-meilisearch.md) | | --- | --- | --- | | Tagline | SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for P | A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications. | | Stars | 1,845 | 58,493 | | Forks | 124 | 2,607 | | Open issues | 30 | 310 | | Language | C | Rust | | Adopt for | - | Meilisearch is a Rust-based, lightning-fast hybrid search engine that integrates easily into web and mobile applications. It supports both full-text and vector searches. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Data & Retrieval, Evaluation & Observability, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [NumKong](/tools/ashvardanian-numkong.md) | [meilisearch](/tools/meilisearch-meilisearch.md) | | --- | --- | --- | | Open issues (now) | 30 | 310 | | Owner type | User | Organization | | Full report | [trust report](/tools/ashvardanian-numkong/trust.md) | [trust report](/tools/meilisearch-meilisearch/trust.md) | ## Decision facts: meilisearch - **Adopt for:** Meilisearch is a Rust-based, lightning-fast hybrid search engine that integrates easily into web and mobile applications. It supports both full-text and vector searches. ## Choose when ### Choose NumKong if… - NumKong is primarily C; meilisearch is Rust. - License: NumKong is Apache-2.0, meilisearch is Other. - Tags unique to NumKong: arm-neon, assembly, blas, cpp. - Also covers Evaluation & Observability. ### Choose meilisearch if… - meilisearch is primarily Rust; NumKong is C. - License: meilisearch is Other, NumKong is Apache-2.0. - Tags unique to meilisearch: ai, api, app-search, database. - meilisearch ships Docker support for self-hosted deployment. - - You require fast integration capabilities for your web or mobile application, as Meilisearch offers flexible deployment options. ## When NOT to use NumKong - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - 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 meilisearch - - When you specifically need language support for a large number of languages beyond what Meilisearch currently offers, as some specialized multilingual search engines might handle more languages nimb - - If your application does not require real-time search-as-you-type or typo tolerance features which can add overhead and may slow down performance in less demanding scenarios. ## Common questions ### What is the difference between NumKong and meilisearch? NumKong: SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for P. meilisearch: A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.. See the comparison table for live GitHub stats and shared categories. ### When should I choose NumKong over meilisearch? Choose NumKong over meilisearch when NumKong is primarily C; meilisearch is Rust; License: NumKong is Apache-2.0, meilisearch is Other; Tags unique to NumKong: arm-neon, assembly, blas, cpp; Also covers Evaluation & Observability. ### When should I choose meilisearch over NumKong? Choose meilisearch over NumKong when meilisearch is primarily Rust; NumKong is C; License: meilisearch is Other, NumKong is Apache-2.0; Tags unique to meilisearch: ai, api, app-search, database; meilisearch ships Docker support for self-hosted deployment; - You require fast integration capabilities for your web or mobile application, as Meilisearch offers flexible deployment options. ### When should I avoid NumKong? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. 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 meilisearch? - When you specifically need language support for a large number of languages beyond what Meilisearch currently offers, as some specialized multilingual search engines might handle more languages nimb - If your application does not require real-time search-as-you-type or typo tolerance features which can add overhead and may slow down performance in less demanding scenarios. ### Is NumKong or meilisearch more popular on GitHub? meilisearch has more GitHub stars (58,493 vs 1,845). Stars measure visibility, not whether either tool fits your constraints. ### Are NumKong and meilisearch open source? Yes - both are open-source projects on GitHub (NumKong: Apache-2.0, meilisearch: Other). ### Where can I find alternatives to NumKong or meilisearch? GraphCanon lists graph-backed alternatives at [NumKong alternatives](/tools/ashvardanian-numkong/alternatives) and [meilisearch alternatives](/tools/meilisearch-meilisearch/alternatives) ([NumKong markdown twin](/tools/ashvardanian-numkong/alternatives.md), [meilisearch markdown twin](/tools/meilisearch-meilisearch/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/ashvardanian-numkong-vs-meilisearch-meilisearch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, NumKong or meilisearch? NumKong: Very active. meilisearch: Very 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 NumKong and meilisearch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [NumKong trust report](/tools/ashvardanian-numkong/trust); [meilisearch trust report](/tools/meilisearch-meilisearch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ashvardanian-numkong`](/api/graphcanon/graph?tool=ashvardanian-numkong) - 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/_