--- title: "awesome-vector-database vs voy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dangkhoasdc-awesome-vector-database-vs-tantaraio-voy" tools: ["dangkhoasdc-awesome-vector-database", "tantaraio-voy"] --- # awesome-vector-database vs voy *GraphCanon updated Aug 23, 2026* ## Verdict Pick awesome-vector-database if a curated list of works on vector databases and high-dimensional structure searching without any implementation details; pick voy if voy specializes in Webassembly-based vector similarity searches, coded in Rust, with support for k-d-trees and nearest-neighbor searching. [awesome-vector-database](https://github.com/dangkhoasdc/awesome-vector-database) reports 359 GitHub stars, 31 forks, and 10 open issues, last pushed Jul 20, 2026. [voy](https://www.npmjs.com/package/voy-search) has 1.1k stars, 41 forks, and 22 open issues, last pushed Sep 20, 2023. Figures are from public GitHub metadata via [awesome-vector-database's repository](https://github.com/dangkhoasdc/awesome-vector-database) and [voy's repository](https://github.com/tantaraio/voy). | | [awesome-vector-database](/tools/dangkhoasdc-awesome-vector-database.md) | [voy](/tools/tantaraio-voy.md) | | --- | --- | --- | | Tagline | A curated list of works on high dimensional structure/vector search and databases | A WASM vector similarity search written in Rust | | Stars | 359 | 1,069 | | Forks | 31 | 41 | | Open issues | 10 | 22 | | Language | - | Rust | | Adopt for | A curated list of works on vector databases and high-dimensional structure searching without any implementation details. | Voy specializes in Webassembly-based vector similarity searches, coded in Rust, with support for k-d-trees and nearest-neighbor searching. | | Persona | - | - | | Runtime | - | - | | License | CC0-1.0 | Apache-2.0 | | Categories | Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-vector-database](/tools/dangkhoasdc-awesome-vector-database.md) | [voy](/tools/tantaraio-voy.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 33d | 1067d | | Open issues (now) | 10 | 22 | | Open issues delta | +4 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/dangkhoasdc-awesome-vector-database/trust.md) | [trust report](/tools/tantaraio-voy/trust.md) | ## Decision facts: awesome-vector-database - **Adopt for:** A curated list of works on vector databases and high-dimensional structure searching without any implementation details. ## Decision facts: voy - **Adopt for:** Voy specializes in Webassembly-based vector similarity searches, coded in Rust, with support for k-d-trees and nearest-neighbor searching. ## Choose when ### Choose awesome-vector-database if… - License: awesome-vector-database is CC0-1.0, voy is Apache-2.0. - Tags unique to awesome-vector-database: approximate-nearest-neighbor-search, embedding-similarity, embeddings-similarity, search-engine. - If you require a comprehensive overview of vector database projects and research papers, as it aggregates information from various sources across the field. ### Choose voy if… - License: voy is Apache-2.0, awesome-vector-database is CC0-1.0. - Tags unique to voy: k-d-tree, rust, wasm, wasm-pack. - When you require a Rust implementation of WebAssembly for embedding in web applications or for secure sandboxed execution on the server-side. ## When NOT to use awesome-vector-database - To find ready-to-use implementations or specific product releases; this repository serves more as a collection of references rather than real-world tools. - If you are looking for direct integration code snippets or detailed tutorials, since the tool is centered on listing and curating resources without delving into practical guides. ## When NOT to use voy - If high availability and extensive fault tolerance features are required, as Voy focuses primarily on vector similarity searches rather than system-wide reliability enhancements. - When your project demands integration with existing large-scale SQL database systems, since Voy is specialized for a specific type of search operation. ## Common questions ### What is the difference between awesome-vector-database and voy? awesome-vector-database: A curated list of works on high dimensional structure/vector search and databases. voy: A WASM vector similarity search written in Rust. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-vector-database over voy? Choose awesome-vector-database over voy when License: awesome-vector-database is CC0-1.0, voy is Apache-2.0; Tags unique to awesome-vector-database: approximate-nearest-neighbor-search, embedding-similarity, embeddings-similarity, search-engine; If you require a comprehensive overview of vector database projects and research papers, as it aggregates information from various sources across the field. ### When should I choose voy over awesome-vector-database? Choose voy over awesome-vector-database when License: voy is Apache-2.0, awesome-vector-database is CC0-1.0; Tags unique to voy: k-d-tree, rust, wasm, wasm-pack; When you require a Rust implementation of WebAssembly for embedding in web applications or for secure sandboxed execution on the server-side. ### When should I avoid awesome-vector-database? To find ready-to-use implementations or specific product releases; this repository serves more as a collection of references rather than real-world tools. If you are looking for direct integration code snippets or detailed tutorials, since the tool is centered on listing and curating resources without delving into practical guides. ### When should I avoid voy? If high availability and extensive fault tolerance features are required, as Voy focuses primarily on vector similarity searches rather than system-wide reliability enhancements. When your project demands integration with existing large-scale SQL database systems, since Voy is specialized for a specific type of search operation. ### Is awesome-vector-database or voy more popular on GitHub? voy has more GitHub stars (1,069 vs 359). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-vector-database and voy open source? Yes - both are open-source projects on GitHub (awesome-vector-database: CC0-1.0, voy: Apache-2.0). ### Where can I find alternatives to awesome-vector-database or voy? GraphCanon lists graph-backed alternatives at [awesome-vector-database alternatives](/tools/dangkhoasdc-awesome-vector-database/alternatives) and [voy alternatives](/tools/tantaraio-voy/alternatives) ([awesome-vector-database markdown twin](/tools/dangkhoasdc-awesome-vector-database/alternatives.md), [voy markdown twin](/tools/tantaraio-voy/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/dangkhoasdc-awesome-vector-database-vs-tantaraio-voy.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-vector-database or voy? awesome-vector-database: Steady. voy: 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 awesome-vector-database and voy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-vector-database trust report](/tools/dangkhoasdc-awesome-vector-database/trust); [voy trust report](/tools/tantaraio-voy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dangkhoasdc-awesome-vector-database`](/api/graphcanon/graph?tool=dangkhoasdc-awesome-vector-database) - 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/_