--- title: "meme-search vs cherche" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/neonwatty-meme-search-vs-raphaelsty-cherche" tools: ["neonwatty-meme-search", "raphaelsty-cherche"] --- # meme-search vs cherche *GraphCanon updated Aug 23, 2026* ## Verdict Pick meme-search if meme-search is an open-source meme search engine for self-hosting that uses Python, Ruby and Docker with semantic searching capabilities via machine learning algorithms; pick cherche if cherche is a Python library for implementing neural search capabilities. [meme-search](https://neonwatty.github.io/meme-search/) reports 717 GitHub stars, 27 forks, and 2 open issues, last pushed Aug 5, 2026. [cherche](https://github.com/raphaelsty/cherche) has 332 stars, 14 forks, and 4 open issues, last pushed Jun 1, 2024. Figures are from public GitHub metadata via [meme-search's repository](https://github.com/neonwatty/meme-search) and [cherche's repository](https://github.com/raphaelsty/cherche). | | [meme-search](/tools/neonwatty-meme-search.md) | [cherche](/tools/raphaelsty-cherche.md) | | --- | --- | --- | | Tagline | An open-source meme search engine designed for self-hosting using Python, Ruby and Docker. | Neural Search | | Stars | 717 | 332 | | Forks | 27 | 14 | | Open issues | 2 | 4 | | Language | Ruby | Python | | Adopt for | meme-search is an open-source meme search engine for self-hosting that uses Python, Ruby and Docker with semantic searching capabilities via machine learning algorithms. | Cherche is a Python library for implementing neural search capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Evaluation & Observability, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [meme-search](/tools/neonwatty-meme-search.md) | [cherche](/tools/raphaelsty-cherche.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 16d | 812d | | Open issues (now) | 2 | 4 | | Stars delta | +22 (30d) | 0 (30d) | | Open issues delta | +2 (30d) | 0 (30d) | | Full report | [trust report](/tools/neonwatty-meme-search/trust.md) | [trust report](/tools/raphaelsty-cherche/trust.md) | ## Shared compatibility - **Python**: [meme-search](/tools/neonwatty-meme-search.md) - Python runtime; [cherche](/tools/raphaelsty-cherche.md) - Python runtime ## Decision facts: meme-search - **Adopt for:** meme-search is an open-source meme search engine for self-hosting that uses Python, Ruby and Docker with semantic searching capabilities via machine learning algorithms. ## Decision facts: cherche - **Adopt for:** Cherche is a Python library for implementing neural search capabilities. ## Choose when ### Choose meme-search if… - meme-search is primarily Ruby; cherche is Python. - License: meme-search is Apache-2.0, cherche is MIT. - Tags unique to meme-search: ai, docker, homelab, meme. - meme-search ships Docker support for self-hosted deployment. - You require a specialized tool designed to specifically locate memes in your collection or the web using a self-hosted solution. ### Choose cherche if… - cherche is primarily Python; meme-search is Ruby. - License: cherche is MIT, meme-search is Apache-2.0. - Tags unique to cherche: bm25, flashtext, information-retrieval, natural-language-processing. - Also covers Evaluation & Observability. - Cherche is a Python library for implementing neural search capabilities. ## When NOT to use meme-search - The need arises for a ready-to-use cloud-based service without managing local hosting configurations, as meme-search requires setting up locally using Docker. - If the focus is on general-purpose data retrieval or vector database management that does not involve memes or specific self-hosted setups. ## When NOT to use cherche - Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. - 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. ## Common questions ### What is the difference between meme-search and cherche? meme-search: An open-source meme search engine designed for self-hosting using Python, Ruby and Docker.. cherche: Neural Search. See the comparison table for live GitHub stats and shared categories. ### When should I choose meme-search over cherche? Choose meme-search over cherche when meme-search is primarily Ruby; cherche is Python; License: meme-search is Apache-2.0, cherche is MIT; Tags unique to meme-search: ai, docker, homelab, meme; meme-search ships Docker support for self-hosted deployment; You require a specialized tool designed to specifically locate memes in your collection or the web using a self-hosted solution. ### When should I choose cherche over meme-search? Choose cherche over meme-search when cherche is primarily Python; meme-search is Ruby; License: cherche is MIT, meme-search is Apache-2.0; Tags unique to cherche: bm25, flashtext, information-retrieval, natural-language-processing; Also covers Evaluation & Observability; Cherche is a Python library for implementing neural search capabilities. ### When should I avoid meme-search? The need arises for a ready-to-use cloud-based service without managing local hosting configurations, as meme-search requires setting up locally using Docker. If the focus is on general-purpose data retrieval or vector database management that does not involve memes or specific self-hosted setups. ### When should I avoid cherche? Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. 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. ### Is meme-search or cherche more popular on GitHub? meme-search has more GitHub stars (717 vs 332). Stars measure visibility, not whether either tool fits your constraints. ### Are meme-search and cherche open source? Yes - both are open-source projects on GitHub (meme-search: Apache-2.0, cherche: MIT). ### Where can I find alternatives to meme-search or cherche? GraphCanon lists graph-backed alternatives at [meme-search alternatives](/tools/neonwatty-meme-search/alternatives) and [cherche alternatives](/tools/raphaelsty-cherche/alternatives) ([meme-search markdown twin](/tools/neonwatty-meme-search/alternatives.md), [cherche markdown twin](/tools/raphaelsty-cherche/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/neonwatty-meme-search-vs-raphaelsty-cherche.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, meme-search or cherche? meme-search: Active. cherche: Dormant. 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 meme-search and cherche? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [meme-search trust report](/tools/neonwatty-meme-search/trust); [cherche trust report](/tools/raphaelsty-cherche/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=neonwatty-meme-search`](/api/graphcanon/graph?tool=neonwatty-meme-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/_