Overview

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Stop stitching three databases together. HelixDB is a Rust-native graph plus vector engine that holds your nodes, your embeddings, your typed edges, and your key-value documents in one process — no separate Postgres, no separate Qdrant, no separate Neo4j. This course walks a Rust-fluent engineer from helix init through a typed HelixQL schema, the helix check and helix compile pre-deploy gates, side-by-side graph traversal and vector search in the same query language, and a typed Rust client that calls a live HelixDB instance with four runtime contracts. Every primitive you meet is wired into a working .hx schema and a running engine you can install in one command. Module 4 puts graph traversal verbs (Out, In, WHERE, ORDER, RANGE) and vector top-k search side by side in the same query language, and adds ShortestPathDijkstras with composable weight expressions for cost-aware routing. You finish with the canonical hybrid-RAG pattern — SearchV returns top-k embeddings, then a typed edge climbs back to the source documents — shipped as a typed Rust client (helix-rs plus serde) with four runtime assertion contracts. The course closes with an honest read on where HelixDB is the wrong choice: columnar OLAP, Spark execution semantics, multi-tenant analytical warehouses.

Syllabus

Why HelixDB

The unified-engine pitch — why one process holding graph + vector + KV + document beats stitching Postgres, Qdrant, and Neo4j at the application layer. You will see the four-layer Helix stack and the honest boundary where HelixDB is the wrong choice.

HelixQL Schema and Your First Queries

The three-element schema in HelixQL and the four-keyword QUERY shape. Walks N::, V::, E:: declarations, INDEX + UNIQUE INDEX, field types, default values, and a queries.hx file end to end.

helix-cli from Init to Push

The helix-cli pipeline walked verb by verb. helix init scaffolds the project; helix check is the lint pass; helix compile is the type-safe lower-to-Rust artifact; helix push dev deploys to a local instance on port 6969 where every QUERY becomes an HTTP endpoint.

Graph Traversal and Vector Search Side by Side

Graph traversal (Out, In, WHERE, ORDER, RANGE) and vector search (SearchV) in the same query language. ShortestPathDijkstras with composable weight expressions (ADD, MUL, POW, SQRT) for cost-aware routing.

Hybrid RAG and a Typed Rust Client

The canonical hybrid-RAG schema (Doc → Embedding → EmbeddingOf) and the hit-to-context traversal. BM25 plus vector reciprocal-rank fusion via the built-in reranker. Closes with a typed Rust client that validates four runtime contracts against a live HelixDB instance.

Critical Thinking

Synthesize what you learned across the course. A short reading prepares you for the graded quiz, followed by a 5-question scenario-based assessment that connects schema design, helix-cli, traversal, vector search, and the hybrid-RAG client. Closes with next steps and references.