--- title: "aquila vs osgrep" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aquila-network-aquila-vs-ryandonofrio3-osgrep" tools: ["aquila-network-aquila", "ryandonofrio3-osgrep"] --- # aquila vs osgrep *GraphCanon updated Aug 22, 2026* ## Verdict Pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches; pick osgrep if osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. [aquila](https://aquila.network) reports 379 GitHub stars, 26 forks, and 13 open issues, last pushed May 6, 2024. [osgrep](https://github.com/Ryandonofrio3/osgrep) has 1.1k stars, 67 forks, and 21 open issues, last pushed Jan 17, 2026. Figures are from public GitHub metadata via [aquila's repository](https://github.com/Aquila-Network/aquila) and [osgrep's repository](https://github.com/Ryandonofrio3/osgrep). | | [aquila](/tools/aquila-network-aquila.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Tagline | Efficient Neural Search Engine | Open Source Semantic Search for your AI Agent | | Stars | 379 | 1,139 | | Forks | 26 | 67 | | Open issues | 13 | 21 | | Language | HTML | TypeScript | | Adopt for | Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. | osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. | | Persona | - | - | | Runtime | - | - | | License | - | osgrep is available under the Apache-2.0 license, offering permissive use for both commercial and non-commercial projects without requiring derivative works to be open-sourced. | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aquila](/tools/aquila-network-aquila.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 817d | 216d | | Open issues (now) | 13 | 21 | | Stars delta | Unknown | -1 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/aquila-network-aquila/trust.md) | [trust report](/tools/ryandonofrio3-osgrep/trust.md) | ## Decision facts: aquila - **Adopt for:** Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. ## Decision facts: osgrep - **Adopt for:** osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. - **License detail:** osgrep is available under the Apache-2.0 license, offering permissive use for both commercial and non-commercial projects without requiring derivative works to be open-sourced. ## Choose when ### Choose aquila if… - aquila is primarily HTML; osgrep is TypeScript. - Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors. - Also covers Vector Databases. - When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary ### Choose osgrep if… - osgrep is primarily TypeScript; aquila is HTML. - Tags unique to osgrep: colbert, embeddings, grep-search. - osgrep ships an MCP server manifest. - - You need advanced semantic search functionality tailored to work seamlessly with your AI agent. ## When NOT to use aquila - If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration - In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ## When NOT to use osgrep - - If your search requirements can be met with simple keyword matching rather than semantic analysis, as osgrep specializes in more complex semantic searches. - - Your AI project is not using TypeScript or where seamless integration with TypeScript-specific features of osgrep would offer no advantage. - - You require additional proprietary functionalities that go beyond what the open-source license and community provide. ## Common questions ### What is the difference between aquila and osgrep? aquila: Efficient Neural Search Engine. osgrep: Open Source Semantic Search for your AI Agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose aquila over osgrep? Choose aquila over osgrep when aquila is primarily HTML; osgrep is TypeScript; Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors; Also covers Vector Databases; When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary. ### When should I choose osgrep over aquila? Choose osgrep over aquila when osgrep is primarily TypeScript; aquila is HTML; Tags unique to osgrep: colbert, embeddings, grep-search; osgrep ships an MCP server manifest; - You need advanced semantic search functionality tailored to work seamlessly with your AI agent. ### When should I avoid aquila? If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ### When should I avoid osgrep? - If your search requirements can be met with simple keyword matching rather than semantic analysis, as osgrep specializes in more complex semantic searches. - Your AI project is not using TypeScript or where seamless integration with TypeScript-specific features of osgrep would offer no advantage. - You require additional proprietary functionalities that go beyond what the open-source license and community provide. ### Is aquila or osgrep more popular on GitHub? osgrep has more GitHub stars (1,139 vs 379). Stars measure visibility, not whether either tool fits your constraints. ### Are aquila and osgrep open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to aquila or osgrep? GraphCanon lists graph-backed alternatives at [aquila alternatives](/tools/aquila-network-aquila/alternatives) and [osgrep alternatives](/tools/ryandonofrio3-osgrep/alternatives) ([aquila markdown twin](/tools/aquila-network-aquila/alternatives.md), [osgrep markdown twin](/tools/ryandonofrio3-osgrep/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/aquila-network-aquila-vs-ryandonofrio3-osgrep.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aquila or osgrep? aquila: Dormant. osgrep: 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 aquila and osgrep? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aquila trust report](/tools/aquila-network-aquila/trust); [osgrep trust report](/tools/ryandonofrio3-osgrep/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aquila-network-aquila`](/api/graphcanon/graph?tool=aquila-network-aquila) - 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/_