Category:

Vector Database

Category:

Retrieval & RAG

Stores embeddings for semantic search and similarity retrieval.

Vector DBs enable similarity search across large embedding datasets—critical for RAG, search, and agent memory systems.

Text → Embedding → Vector Store → Similarity Search → LLM

Embedding index, HNSW graphs, metadata filters, vector search engine

RAG retrieval, semantic search, memory systems, recommendations

Wrong distance metrics, irrelevant chunks, slow retrieval latency

Vector Search, Embedding Database

• Embeddings
• Chunking
• Reranking
• Semantic Search

• Vector DB comparison framework