Moving Off Memgraph: Migrating Agent Memory to HelixDB
Moving off Memgraph for agent memory? Audit your Cypher schema, export it cleanly, and rewrite retrieval so graph traversal, vector search and BM25 run in one query.
12 min read
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Agent Content
Technical guides and practical insights for building AI systems.
Semantic Search Over Internal Documents Is Not Enough
Semantic search over internal documents misses answers that live in a relationship rather than a chunk. Here is what a graph-vector engine does instead.
11 min read
Open Source Graph Database Written in Rust: How HelixDB Is Built
HelixDB is an open source graph database written in Rust that runs graph traversal, vector search and BM25 full-text in one engine. Here is how it is built.
13 min read
How to Give AI Agents Persistent Memory in One Database
Give AI agents memory that survives restarts: model episodes as timestamped nodes and edges, then scope semantic recall to one user with a graph traversal.
13 min read
How to Build a GraphRAG Pipeline: From Documents to Scoped Retrieval
Learn how to build a GraphRAG pipeline to solve multi-hop Q&A. This guide covers entity extraction, graph modeling, and scoped retrieval using HelixDB.
10 min read
HelixDB vs LadybugDB: Picking a Graph DB After Kuzu
Kuzu is archived. LadybugDB is columnar and analytical, in-process or in the browser. HelixDB is OLTP agent memory with pre-filtered vector and keyword search.
11 min read
How to Migrate from Neo4j to HelixDB: A Migration Guide
Migrate from Neo4j to HelixDB: map the graph, export a checksummed snapshot, load it with replay-safe batches, translate your Cypher, and verify before cutover.
20 min read
Pre-Filtering Vector Search on Graph Edges: How to Scope ANN to Relationships
Learn how to scope vector search on graph edges for precise RAG. Move beyond flat ANN scans by filtering embeddings within specific relationships and subgraphs.
12 min read
HelixDB vs FalkorDB: Choosing a Graph Database for GraphRAG
HelixDB vs FalkorDB for GraphRAG: in-memory speed against object-storage scale. Compare pre-filtering, high availability, licensing and what each one costs.
16 min read
Vector Database vs Graph Database: What AI Memory Needs
An architectural comparison of vector vs graph databases for AI memory. Learn why HelixDB replaces the duct-taped RAG stack with a single Rust engine.
11 min read
HelixDB vs Memgraph: Which Graph Database for AI Memory?
HelixDB vs Memgraph: in-memory graph analytics against object-storage-backed agent memory. Which one actually scales, and what does each one cost to run?
19 min read
HelixDB vs Neo4j: Graph and Vector Search in One Engine
Compare HelixDB vs Neo4j for GraphRAG and agent memory. Learn why a unified Rust engine beats a bolted-on vector approach for high-performance AI applications.
13 min read
AI Agent Memory Architecture: Why Vector Search Is Not Enough
Learn why modern AI agent memory architecture requires knowledge graphs. Compare GraphRAG vs. vector search and see how HelixDB unifies both in one Rust engine.
11 min read