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Learn about graph databases

A graph database stores entities as nodes and relationships as edges, so questions about how things connect are direct to ask.
What is a graph database? What is the difference between a graph database and a relational database? What is a knowledge graph? What is a property graph? What is the difference between a property graph and RDF?

Learn about vector search

Vector search finds items by meaning, comparing embeddings instead of matching words. It powers semantic search, recommendations, and retrieval for LLMs.
What is vector search? What are vector embeddings? What is a vector database? What is HNSW? What is filtered vector search? What is the difference between cosine, Euclidean, and Manhattan distance?

Learn about full-text search

Full-text search ranks documents by the words they contain. It finds exact names, IDs, and rare terms that embeddings tend to blur.
What is full-text search? What is BM25? What is hybrid search?

Learn about AI memory and RAG

Retrieval and memory give a language model the right context: relevant documents for each question, and what it knows about users and past conversations.
What is retrieval-augmented generation (RAG)? What is GraphRAG? What is AI agent memory? How do you build long-term memory for AI agents?

Learn about database architecture

Where a database keeps its data decides how far it scales and what it costs. Separating storage from compute changes both.
Why build a database on object storage? Do you need separate graph, vector, and text databases?

Build with HelixDB

HelixDB is an open-source graph database with native vector search and BM25 full-text search, built on object storage.
Get started in a few commands Read the introduction Understand the data model