--- title: "oasysdb vs meilisearch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/edwinkys-oasysdb-vs-meilisearch-meilisearch" tools: ["edwinkys-oasysdb", "meilisearch-meilisearch"] --- # oasysdb vs meilisearch *GraphCanon updated Jul 11, 2026* ## Verdict Pick oasysdb when license: oasysdb is Apache-2.0, meilisearch is Other; pick meilisearch when license: meilisearch is Other, oasysdb is Apache-2.0. [oasysdb](https://github.com/edwinkys/oasysdb) reports 375 GitHub stars, 14 forks, and 0 open issues, last pushed Nov 29, 2024. [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 [oasysdb's repository](https://github.com/edwinkys/oasysdb) and [meilisearch's repository](https://github.com/meilisearch/meilisearch). | | [oasysdb](/tools/edwinkys-oasysdb.md) | [meilisearch](/tools/meilisearch-meilisearch.md) | | --- | --- | --- | | Tagline | In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching. | A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications. | | Stars | 375 | 58,493 | | Forks | 14 | 2,607 | | Open issues | 0 | 310 | | Language | Rust | 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, Vector Databases, Evaluation & Observability | Vector Databases, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [oasysdb](/tools/edwinkys-oasysdb.md) | [meilisearch](/tools/meilisearch-meilisearch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 589d | 1d | | Open issues (now) | 0 | 310 | | Owner type | User | Organization | | Full report | [trust report](/tools/edwinkys-oasysdb/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 oasysdb if… - License: oasysdb is Apache-2.0, meilisearch is Other. - Tags unique to oasysdb: postgresql, similarity-search, ivfpq, rust. - Also covers Evaluation & Observability. ### Choose meilisearch if… - License: meilisearch is Other, oasysdb is Apache-2.0. - Tags unique to meilisearch: app-search, full-text-search, ai, enterprise-search. - 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 oasysdb - Last GitHub push was 590 days ago (dormant maintenance, Nov 29, 2024). Validate activity before betting a new project on oasysdb. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## 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 oasysdb and meilisearch? oasysdb: In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.. 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 oasysdb over meilisearch? Choose oasysdb over meilisearch when License: oasysdb is Apache-2.0, meilisearch is Other; Tags unique to oasysdb: postgresql, similarity-search, ivfpq, rust; Also covers Evaluation & Observability. ### When should I choose meilisearch over oasysdb? Choose meilisearch over oasysdb when License: meilisearch is Other, oasysdb is Apache-2.0; Tags unique to meilisearch: app-search, full-text-search, ai, enterprise-search; 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 oasysdb? Last GitHub push was 590 days ago (dormant maintenance, Nov 29, 2024). Validate activity before betting a new project on oasysdb. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### 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 oasysdb or meilisearch more popular on GitHub? meilisearch has more GitHub stars (58,493 vs 375). Stars measure visibility, not whether either tool fits your constraints. ### Are oasysdb and meilisearch open source? Yes - both are open-source projects on GitHub (oasysdb: Apache-2.0, meilisearch: Other). ### Where can I find alternatives to oasysdb or meilisearch? GraphCanon lists graph-backed alternatives at [oasysdb alternatives](/tools/edwinkys-oasysdb/alternatives) and [meilisearch alternatives](/tools/meilisearch-meilisearch/alternatives) ([oasysdb markdown twin](/tools/edwinkys-oasysdb/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/edwinkys-oasysdb-vs-meilisearch-meilisearch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, oasysdb or meilisearch? oasysdb: Dormant. 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 oasysdb and meilisearch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [oasysdb trust report](/tools/edwinkys-oasysdb/trust); [meilisearch trust report](/tools/meilisearch-meilisearch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=edwinkys-oasysdb`](/api/graphcanon/graph?tool=edwinkys-oasysdb) - 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/_