AI Data Infrastructure

Vector Databases & RAG

Vector Databases & RAG guides, comparisons and explainers from AIDataCloudBase.

Documents split into chunks for RAG retrieval

Vector Databases & RAG Nov 4, 2026 · 8 min read

Chunking Strategies for RAG: How to Split Documents Before Embedding

A practical guide to chunking documents for retrieval-augmented generation: fixed, structural, and semantic splitting, overlap, and how to test your choice.

Debugging retrieval quality in a RAG pipeline

Vector Databases & RAG Nov 4, 2026 · 8 min read

Why Your RAG Answers Are Wrong: Debugging Retrieval Quality

A layered approach to debugging weak RAG answers: separate retrieval failures from generation failures, then fix chunking, embeddings, and ranking.

Selecting a vector database for retrieval-augmented generation

Vector Databases & RAG Nov 4, 2026 · 8 min read

How to Choose a Vector Database for a RAG Application

A practical framework for picking a vector database for retrieval-augmented generation: filtering, hybrid search, operations, and fit with your existing stack.

Source documents syncing into a vector index

Vector Databases & RAG Nov 4, 2026 · 8 min read

Keeping a Vector Index in Sync When Your Source Data Keeps Changing

How to keep a RAG vector index fresh as documents are edited, moved, and deleted, with change detection, upserts, and stale-content checks.