Retrieve

Pull the right outside knowledge into context, just in time: search, RAG, embeddings, rerankers, docs and code fetchers.

30 listed entries

Milvus

Cloud-native vector database built for large-scale approximate nearest-neighbor search.

tool

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

Screenshot of the GraphRAG website

GraphRAG

Microsoft's graph-based RAG: builds a knowledge graph and community summaries to answer whole-corpus questions.

tool

Website captured Oct 19

Screenshot of the Qdrant website

Qdrant

Open-source vector database and search engine for semantic and hybrid retrieval at scale.

tool

Website captured Oct 19

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

Screenshot of the Chroma website

Chroma

Open-source search infrastructure for AI: embed, store and query documents for retrieval.

tool

Website captured Oct 19

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

pgvector

Vector similarity search inside Postgres, so retrieval lives next to your app data.

tool

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

Screenshot of the Weaviate website

Weaviate

Open-source vector database that combines vector search with structured filtering.

tool

Website captured Oct 19

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

Screenshot of the LanceDB website

LanceDB

Embedded retrieval library for multimodal data: vector, full-text and hybrid search inside your process.

tool

Website captured Oct 19

Disclosure: the operator of shipping.buzz is a Qdrant Star Ambassador. No manual overrides apply to vector databases.

Screenshot of the BGE-M3 website

BGE-M3

Multilingual embedding model that does dense, sparse and multi-vector retrieval in one model (BAAI).

tool

Website captured Oct 19

Contextual retrieval

Prepend chunk-specific context before embedding and BM25 indexing. Anthropic measured 49% fewer failed retrievals, and 67% fewer with reranking.

process

    Just-in-time retrieval

    Keep lightweight references (file paths, stored queries, links) in context and load the data with tools only when it's needed.

    process

      How they connect