{"data":{"node":{"slug":"dingodb-dingo","name":"dingo","tagline":"A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data","github_url":"https://github.com/dingodb/dingo","owner":"dingodb","repo":"dingo","owner_avatar_url":"https://avatars.githubusercontent.com/u/91237812?v=4","primary_language":"Java","stars":1701,"forks":265,"topics":["embedding-search","embedding-store","hybrid-search","key-value-distributed-store","mysql-compatibility","real-time-semantic-search","serving","structured-data","unified-sql","unstructured-data","vector-database","vector-ocean"],"archived":false,"github_pushed_at":"2026-07-10T11:13:29+00:00","maintenance_label":"Steady","stars_delta_30d":2,"url":"https://www.graphcanon.com/tools/dingodb-dingo","markdown_url":"https://www.graphcanon.com/tools/dingodb-dingo.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/dingodb-dingo","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=dingodb-dingo"},"categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"embedding-search","name":"embedding-search"},{"slug":"embedding-store","name":"embedding-store"},{"slug":"hybrid-search","name":"hybrid-search"},{"slug":"key-value-distributed-store","name":"key-value-distributed-store"},{"slug":"mysql-compatibility","name":"mysql-compatibility"},{"slug":"real-time-semantic-search","name":"real-time-semantic-search"},{"slug":"serving","name":"serving"},{"slug":"structured-data","name":"structured-data"}],"edges":[{"type":"alternative","direction":"out","explanation":"Dingo and Qdrant both are vector databases supporting high-performance similarity searches, but Dingo additionally supports SQL-like query capabilities and integrates relational semantics.","successor_context":null,"tool":{"slug":"qdrant-qdrant","name":"qdrant","tagline":"High-performance, massive-scale Vector Database and Vector Search Engine","github_url":"https://github.com/qdrant/qdrant","owner":"qdrant","repo":"qdrant","owner_avatar_url":"https://avatars.githubusercontent.com/u/73504361?v=4","primary_language":"Rust","stars":33629,"forks":2529,"topics":["ai-search","ai-search-engine","embeddings-similarity","hnsw","hybrid-search","image-search","knn-algorithm","machine-learning","mlops","nearest-neighbor-search","neural-network","neural-search","recommender-system","search","search-engine","search-engines","similarity-search","vector-database","vector-search","vector-search-engine"],"archived":false,"github_pushed_at":"2026-07-28T17:03:13+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/qdrant-qdrant","markdown_url":"https://www.graphcanon.com/tools/qdrant-qdrant.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/qdrant-qdrant","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=qdrant-qdrant"}},{"type":"alternative","direction":"out","explanation":"Both DingoDB and LanceDB serve as multi-modal vector databases, offering solutions for embedding storage and search. They compete by providing similar functionalities but may approach the problem differently.","successor_context":null,"tool":{"slug":"lancedb-lancedb","name":"lancedb","tagline":"Developer-friendly OSS embedded retrieval library for multimodal AI.","github_url":"https://github.com/lancedb/lancedb","owner":"lancedb","repo":"lancedb","owner_avatar_url":"https://avatars.githubusercontent.com/u/108903835?v=4","primary_language":"Rust","stars":11014,"forks":972,"topics":["approximate-nearest-neighbor-search","image-search","nearest-neighbor-search","recommender-system","search-engine","semantic-search","similarity-search","vector-database"],"archived":false,"github_pushed_at":"2026-07-28T17:22:39+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/lancedb-lancedb","markdown_url":"https://www.graphcanon.com/tools/lancedb-lancedb.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lancedb-lancedb","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lancedb-lancedb"}},{"type":"related","direction":"out","explanation":"Databend is a data warehouse for AI agents, whereas DingoDB focuses on being a multi-modal vector database offering high-level SQL access and real-time strong consistency among other features. They serve related but distinct purposes within the same ecosystem.","successor_context":null,"tool":{"slug":"databendlabs-databend","name":"databend","tagline":"All-in-One Data Warehouse: Analytics, Search, AI, and Python Sandboxing Reimagined From Scratch.","github_url":"https://github.com/databendlabs/databend","owner":"databendlabs","repo":"databend","owner_avatar_url":"https://avatars.githubusercontent.com/u/80994548?v=4","primary_language":"Rust","stars":9420,"forks":891,"topics":["ai","bigdata","cloud-native","database","elasticsearch","geospatial","lakehouse","olap","rust","serverless","snowflake","sql","vector-database","vector-search"],"archived":false,"github_pushed_at":"2026-08-21T05:00:06+00:00","maintenance_label":"Very active","stars_delta_30d":31,"url":"https://www.graphcanon.com/tools/databendlabs-databend","markdown_url":"https://www.graphcanon.com/tools/databendlabs-databend.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/databendlabs-databend","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=databendlabs-databend"}},{"type":"integrates_with","direction":"out","explanation":"DingoDB can be part of RAG (Retrieval-Augmented Generation) and enterprise search pipelines, similar to the focus areas supported by llm-app.","successor_context":null,"tool":{"slug":"pathwaycom-llm-app","name":"llm-app","tagline":"Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.","github_url":"https://github.com/pathwaycom/llm-app","owner":"pathwaycom","repo":"llm-app","owner_avatar_url":"https://avatars.githubusercontent.com/u/25750857?v=4","primary_language":"Jupyter Notebook","stars":59037,"forks":1466,"topics":["chatbot","hugging-face","llm","llm-local","llm-prompting","llm-security","llmops","machine-learning","open-ai","pathway","rag","real-time","retrieval-augmented-generation","vector-database","vector-index"],"archived":false,"github_pushed_at":"2026-07-05T17:59:07+00:00","maintenance_label":"Steady","stars_delta_30d":11,"url":"https://www.graphcanon.com/tools/pathwaycom-llm-app","markdown_url":"https://www.graphcanon.com/tools/pathwaycom-llm-app.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/pathwaycom-llm-app","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=pathwaycom-llm-app"}},{"type":"alternative","direction":"out","explanation":"Milvus is a high-performance cloud-native vector database for scalable ANN search, competing in the space of vector database services and thus serving as an alternative to DingoDB.","successor_context":null,"tool":{"slug":"milvus-io-milvus","name":"milvus","tagline":"High-performance cloud-native vector database","github_url":"https://github.com/milvus-io/milvus","owner":"milvus-io","repo":"milvus","owner_avatar_url":"https://avatars.githubusercontent.com/u/51735404?v=4","primary_language":"Go","stars":45402,"forks":4147,"topics":["anns","cloud-native","diskann","distributed","embedding-database","embedding-similarity","embedding-store","faiss","golang","hnsw","image-search","llm","nearest-neighbor-search","rag","vector-database","vector-search","vector-similarity","vector-store"],"archived":false,"github_pushed_at":"2026-07-28T17:42:13+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/milvus-io-milvus","markdown_url":"https://www.graphcanon.com/tools/milvus-io-milvus.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/milvus-io-milvus","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=milvus-io-milvus"}},{"type":"related","direction":"out","explanation":"While Chroma focuses on a more general purpose search infrastructure for AI, DingoDB is specifically built as a vector database that can be used in similar scenarios.","successor_context":null,"tool":{"slug":"chroma-core-chroma","name":"chroma","tagline":"Search infrastructure for AI","github_url":"https://github.com/chroma-core/chroma","owner":"chroma-core","repo":"chroma","owner_avatar_url":"https://avatars.githubusercontent.com/u/105881770?v=4","primary_language":"Rust","stars":28898,"forks":2409,"topics":["agents","ai","ai-agents","database","rust","rust-lang"],"archived":false,"github_pushed_at":"2026-07-27T22:15:20+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/chroma-core-chroma","markdown_url":"https://www.graphcanon.com/tools/chroma-core-chroma.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/chroma-core-chroma","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=chroma-core-chroma"}},{"type":"related","direction":"out","explanation":"DingoDB is a vector database that provides similar features to what would be tested by VectorDBBench. However, since they do not directly integrate or succeed each other but are rather separate tools in the space of vector databases and their benchmarks.","successor_context":null,"tool":{"slug":"zilliztech-vectordbbench","name":"VectorDBBench","tagline":"Benchmark for vector databases","github_url":"https://github.com/zilliztech/VectorDBBench","owner":"zilliztech","repo":"VectorDBBench","owner_avatar_url":"https://avatars.githubusercontent.com/u/18416694?v=4","primary_language":"Python","stars":1164,"forks":425,"topics":["benchmark","cost-effectiveness","performance","vector-database","vector-search","vectordb"],"archived":false,"github_pushed_at":"2026-08-14T10:00:47+00:00","maintenance_label":"Active","stars_delta_30d":17,"url":"https://www.graphcanon.com/tools/zilliztech-vectordbbench","markdown_url":"https://www.graphcanon.com/tools/zilliztech-vectordbbench.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/zilliztech-vectordbbench","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=zilliztech-vectordbbench"}},{"type":"alternative","direction":"out","explanation":"Both Dingo and pgVector extend databases with vector search capabilities, although Dingo focuses specifically on a multi-modal database system with SQL support.","successor_context":null,"tool":{"slug":"pgvector-pgvector","name":"pgvector","tagline":"Open-source vector similarity search for Postgres","github_url":"https://github.com/pgvector/pgvector","owner":"pgvector","repo":"pgvector","owner_avatar_url":"https://avatars.githubusercontent.com/u/98363230?v=4","primary_language":"C","stars":22375,"forks":1257,"topics":["approximate-nearest-neighbor-search","nearest-neighbor-search"],"archived":false,"github_pushed_at":"2026-07-28T09:49:19+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/pgvector-pgvector","markdown_url":"https://www.graphcanon.com/tools/pgvector-pgvector.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/pgvector-pgvector","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=pgvector-pgvector"}},{"type":"related","direction":"out","explanation":"DingoDB supports hybrid searching, just like MeiliSearch; however, DingoDB's core focus is on a multi-modal database rather than a general-purpose search engine.","successor_context":null,"tool":{"slug":"meilisearch-meilisearch","name":"meilisearch","tagline":"A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.","github_url":"https://github.com/meilisearch/meilisearch","owner":"meilisearch","repo":"meilisearch","owner_avatar_url":"https://avatars.githubusercontent.com/u/43250847?v=4","primary_language":"Rust","stars":59034,"forks":2672,"topics":["ai","api","app-search","database","enterprise-search","faceting","full-text-search","fuzzy-search","geosearch","hybrid-search","instantsearch","search","search-as-you-type","search-engine","semantic-search","site-search","typo-tolerance","vector-database","vector-search","vectors"],"archived":false,"github_pushed_at":"2026-08-14T09:38:01+00:00","maintenance_label":"Very active","stars_delta_30d":352,"url":"https://www.graphcanon.com/tools/meilisearch-meilisearch","markdown_url":"https://www.graphcanon.com/tools/meilisearch-meilisearch.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/meilisearch-meilisearch","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=meilisearch-meilisearch"}}],"neighbours":[{"slug":"milvus-io-milvus","name":"milvus","tagline":"High-performance cloud-native vector database","github_url":"https://github.com/milvus-io/milvus","owner":"milvus-io","repo":"milvus","owner_avatar_url":"https://avatars.githubusercontent.com/u/51735404?v=4","primary_language":"Go","stars":45402,"forks":4147,"topics":["anns","cloud-native","diskann","distributed","embedding-database","embedding-similarity","embedding-store","faiss","golang","hnsw","image-search","llm","nearest-neighbor-search","rag","vector-database","vector-search","vector-similarity","vector-store"],"archived":false,"github_pushed_at":"2026-07-28T17:42:13+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/milvus-io-milvus","markdown_url":"https://www.graphcanon.com/tools/milvus-io-milvus.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/milvus-io-milvus","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=milvus-io-milvus","shared_categories":["vector-databases"]},{"slug":"pingcap-tidb","name":"tidb","tagline":"Scalable, cloud-native database with ACID transactions and vector search support.","github_url":"https://github.com/pingcap/tidb","owner":"pingcap","repo":"tidb","owner_avatar_url":"https://avatars.githubusercontent.com/u/11855343?v=4","primary_language":"Go","stars":40446,"forks":6223,"topics":["agent","agent-context","agent-memory","agentic","ai","cloud-native","database","distributed-database","distributed-transactions","go","hacktoberfest","htap","memory","mysql","mysql-compatibility","scale","serverless","sql","tidb"],"archived":false,"github_pushed_at":"2026-08-18T23:24:30+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/pingcap-tidb","markdown_url":"https://www.graphcanon.com/tools/pingcap-tidb.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/pingcap-tidb","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=pingcap-tidb","shared_categories":["vector-databases","data-retrieval"]},{"slug":"qdrant-qdrant","name":"qdrant","tagline":"High-performance, massive-scale Vector Database and Vector Search Engine","github_url":"https://github.com/qdrant/qdrant","owner":"qdrant","repo":"qdrant","owner_avatar_url":"https://avatars.githubusercontent.com/u/73504361?v=4","primary_language":"Rust","stars":33629,"forks":2529,"topics":["ai-search","ai-search-engine","embeddings-similarity","hnsw","hybrid-search","image-search","knn-algorithm","machine-learning","mlops","nearest-neighbor-search","neural-network","neural-search","recommender-system","search","search-engine","search-engines","similarity-search","vector-database","vector-search","vector-search-engine"],"archived":false,"github_pushed_at":"2026-07-28T17:03:13+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/qdrant-qdrant","markdown_url":"https://www.graphcanon.com/tools/qdrant-qdrant.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/qdrant-qdrant","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=qdrant-qdrant","shared_categories":["vector-databases","data-retrieval"]},{"slug":"pgvector-pgvector","name":"pgvector","tagline":"Open-source vector similarity search for Postgres","github_url":"https://github.com/pgvector/pgvector","owner":"pgvector","repo":"pgvector","owner_avatar_url":"https://avatars.githubusercontent.com/u/98363230?v=4","primary_language":"C","stars":22375,"forks":1257,"topics":["approximate-nearest-neighbor-search","nearest-neighbor-search"],"archived":false,"github_pushed_at":"2026-07-28T09:49:19+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/pgvector-pgvector","markdown_url":"https://www.graphcanon.com/tools/pgvector-pgvector.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/pgvector-pgvector","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=pgvector-pgvector","shared_categories":["vector-databases"]},{"slug":"lancedb-lancedb","name":"lancedb","tagline":"Developer-friendly OSS embedded retrieval library for multimodal AI.","github_url":"https://github.com/lancedb/lancedb","owner":"lancedb","repo":"lancedb","owner_avatar_url":"https://avatars.githubusercontent.com/u/108903835?v=4","primary_language":"Rust","stars":11014,"forks":972,"topics":["approximate-nearest-neighbor-search","image-search","nearest-neighbor-search","recommender-system","search-engine","semantic-search","similarity-search","vector-database"],"archived":false,"github_pushed_at":"2026-07-28T17:22:39+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/lancedb-lancedb","markdown_url":"https://www.graphcanon.com/tools/lancedb-lancedb.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lancedb-lancedb","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lancedb-lancedb","shared_categories":["vector-databases","data-retrieval"]},{"slug":"databendlabs-databend","name":"databend","tagline":"All-in-One Data Warehouse: Analytics, Search, AI, and Python Sandboxing Reimagined From Scratch.","github_url":"https://github.com/databendlabs/databend","owner":"databendlabs","repo":"databend","owner_avatar_url":"https://avatars.githubusercontent.com/u/80994548?v=4","primary_language":"Rust","stars":9420,"forks":891,"topics":["ai","bigdata","cloud-native","database","elasticsearch","geospatial","lakehouse","olap","rust","serverless","snowflake","sql","vector-database","vector-search"],"archived":false,"github_pushed_at":"2026-08-21T05:00:06+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/databendlabs-databend","markdown_url":"https://www.graphcanon.com/tools/databendlabs-databend.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/databendlabs-databend","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=databendlabs-databend","shared_categories":["vector-databases","data-retrieval"]},{"slug":"infiniflow-infinity","name":"infinity","tagline":"AI-native database for LLM applications offering fast hybrid search capabilities.","github_url":"https://github.com/infiniflow/infinity","owner":"infiniflow","repo":"infinity","owner_avatar_url":"https://avatars.githubusercontent.com/u/69962740?v=4","primary_language":"C++","stars":4675,"forks":437,"topics":["ai-native","approximate-nearest-neighbor-search","bm25","cpp20","cpp20-modules","embedding","full-text-search","hnsw","hybrid-search","information-retrival","multi-vector","nearest-neighbor-search","rag","search-engine","tensor-database","vector","vector-database","vector-search","vectordatabase"],"archived":false,"github_pushed_at":"2026-08-17T13:43:09+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/infiniflow-infinity","markdown_url":"https://www.graphcanon.com/tools/infiniflow-infinity.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/infiniflow-infinity","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=infiniflow-infinity","shared_categories":["vector-databases","data-retrieval"]},{"slug":"tensorchord-pgvecto-rs","name":"pgvecto.rs","tagline":"Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres","github_url":"https://github.com/tensorchord/pgvecto.rs","owner":"tensorchord","repo":"pgvecto.rs","owner_avatar_url":"https://avatars.githubusercontent.com/u/100543303?v=4","primary_language":"Rust","stars":2183,"forks":86,"topics":["chatgpt","faiss","gpt","hacktoberfest","llm","nearest-neighbor-search","postgres","rust","vector","vector-database"],"archived":false,"github_pushed_at":"2025-02-26T14:11:43+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/tensorchord-pgvecto-rs","markdown_url":"https://www.graphcanon.com/tools/tensorchord-pgvecto-rs.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/tensorchord-pgvecto-rs","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=tensorchord-pgvecto-rs","shared_categories":["vector-databases"]},{"slug":"eosphoros-ai-db-gpt-hub","name":"DB-GPT-Hub","tagline":"Repository for DB-GPT models, datasets, and techniques aimed at Text-to-SQL performance enhancement.","github_url":"https://github.com/eosphoros-ai/DB-GPT-Hub","owner":"eosphoros-ai","repo":"DB-GPT-Hub","owner_avatar_url":"https://avatars.githubusercontent.com/u/140580304?v=4","primary_language":"Python","stars":2001,"forks":250,"topics":["database","datasets","fine-tuning","gpt","hacktoberfest","llm","nl2sql","sql","text-to-sql","text2sql"],"archived":false,"github_pushed_at":"2025-07-02T03:39:31+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/eosphoros-ai-db-gpt-hub","markdown_url":"https://www.graphcanon.com/tools/eosphoros-ai-db-gpt-hub.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/eosphoros-ai-db-gpt-hub","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=eosphoros-ai-db-gpt-hub","shared_categories":[]},{"slug":"matrixorigin-matrixone","name":"matrixone","tagline":"AI-native HTAP database with Git-for-Data and built-in vector search","github_url":"https://github.com/matrixorigin/matrixone","owner":"matrixorigin","repo":"matrixone","owner_avatar_url":"https://avatars.githubusercontent.com/u/76932962?v=4","primary_language":"Go","stars":1879,"forks":308,"topics":["agents","ai-native","cloud-native","database","distributed-database","distributed-systems","fulltext-support","git-for-data","go","htap","hyperconverged","memory","mysql-compatible","olap","one-size-fits-all","sql","vector-database"],"archived":false,"github_pushed_at":"2026-08-21T11:31:20+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/matrixorigin-matrixone","markdown_url":"https://www.graphcanon.com/tools/matrixorigin-matrixone.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/matrixorigin-matrixone","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=matrixorigin-matrixone","shared_categories":["vector-databases","data-retrieval"]},{"slug":"milvus-io-pymilvus","name":"pymilvus","tagline":"Python SDK for Milvus Vector Database","github_url":"https://github.com/milvus-io/pymilvus","owner":"milvus-io","repo":"pymilvus","owner_avatar_url":"https://avatars.githubusercontent.com/u/51735404?v=4","primary_language":"Python","stars":1406,"forks":453,"topics":["anns","faiss","faiss-vector-database","milvus","milvus-lite","milvus-sdk","python","python-sdk","vector-database"],"archived":false,"github_pushed_at":"2026-08-19T07:15:13+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/milvus-io-pymilvus","markdown_url":"https://www.graphcanon.com/tools/milvus-io-pymilvus.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/milvus-io-pymilvus","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=milvus-io-pymilvus","shared_categories":["vector-databases"]},{"slug":"endee-io-endee","name":"endee","tagline":"A high-performance vector database handling up to 1B vectors on one node","github_url":"https://github.com/endee-io/endee","owner":"endee-io","repo":"endee","owner_avatar_url":"https://avatars.githubusercontent.com/u/241616584?v=4","primary_language":"C++","stars":1305,"forks":1663,"topics":["ai-search","ai-search-engine","ann","endee","hnsw","hybrid-search","image-search","vector","vector-database","vector-search-engine"],"archived":false,"github_pushed_at":"2026-07-29T09:56:00+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/endee-io-endee","markdown_url":"https://www.graphcanon.com/tools/endee-io-endee.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/endee-io-endee","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=endee-io-endee","shared_categories":["vector-databases"]}]}}