> ## Documentation Index
> Fetch the complete documentation index at: https://docs.helix-db.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Learning center

> Plain-language answers about graph databases, vector search, full-text search, AI agent memory, and modern database architecture.

<div className="learn-tiles learn-grid">
  <Card title="Learn about graph databases" icon="diagram-project">
    A graph database stores entities as nodes and relationships as edges, so questions
    about how things connect are direct to ask.

    <div className="learn-links">
      [What is a graph database?](/learn/graph-databases/what-is-a-graph-database)
      [What is the difference between a graph database and a relational database?](/learn/graph-databases/graph-vs-relational-database)
      [What is a knowledge graph?](/learn/graph-databases/what-is-a-knowledge-graph)
      [What is a property graph?](/learn/graph-databases/what-is-a-property-graph)
      [What is the difference between a property graph and RDF?](/learn/graph-databases/property-graph-vs-rdf)
    </div>
  </Card>

  <Card title="Learn about vector search" icon="vector-square">
    Vector search finds items by meaning, comparing embeddings instead of matching
    words. It powers semantic search, recommendations, and retrieval for LLMs.

    <div className="learn-links">
      [What is vector search?](/learn/vector-search/what-is-vector-search)
      [What are vector embeddings?](/learn/vector-search/what-are-vector-embeddings)
      [What is a vector database?](/learn/vector-search/what-is-a-vector-database)
      [What is HNSW?](/learn/vector-search/what-is-hnsw)
      [What is filtered vector search?](/learn/vector-search/filtered-vector-search)
      [What is the difference between cosine, Euclidean, and Manhattan distance?](/learn/vector-search/vector-distance-metrics)
    </div>
  </Card>

  <Card title="Learn about full-text search" icon="magnifying-glass">
    Full-text search ranks documents by the words they contain. It finds exact names,
    IDs, and rare terms that embeddings tend to blur.

    <div className="learn-links">
      [What is full-text search?](/learn/full-text-search/what-is-full-text-search)
      [What is BM25?](/learn/full-text-search/what-is-bm25)
      [What is hybrid search?](/learn/full-text-search/hybrid-search)
    </div>
  </Card>

  <Card title="Learn about AI memory and RAG" icon="brain">
    Retrieval and memory give a language model the right context: relevant documents for
    each question, and what it knows about users and past conversations.

    <div className="learn-links">
      [What is retrieval-augmented generation (RAG)?](/learn/ai-memory/what-is-rag)
      [What is GraphRAG?](/learn/ai-memory/what-is-graphrag)
      [What is AI agent memory?](/learn/ai-memory/what-is-ai-agent-memory)
      [How do you build long-term memory for AI agents?](/learn/ai-memory/long-term-memory-for-ai-agents)
    </div>
  </Card>

  <Card title="Learn about database architecture" icon="layer-group">
    Where a database keeps its data decides how far it scales and what it costs.
    Separating storage from compute changes both.

    <div className="learn-links">
      [Why build a database on object storage?](/learn/database-architecture/object-storage-databases)
      [Do you need separate graph, vector, and text databases?](/learn/database-architecture/one-database-for-graph-vector-and-text)
    </div>
  </Card>

  <Card title="Build with HelixDB" icon="rocket">
    HelixDB is an open-source graph database with native vector search and BM25
    full-text search, built on object storage.

    <div className="learn-links">
      [Get started in a few commands](/database/helix-db/start-here/quickstart)
      [Read the introduction](/database/helix-db/start-here/introduction)
      [Understand the data model](/database/helix-db/core-concepts/data-model)
    </div>
  </Card>
</div>