Skip to content

Examples

  1. CSV with Multiple Tabular Sources
  2. JSON with Self-Reference Vertices
  3. CSV with Edge Weights and Multiple Relations
  4. Neo4j Ingestion with Dynamic Relations from Keys
  5. 🚀 PostgreSQL Schema Inference and Ingestion - Automatically infer graph schemas from normalized PostgreSQL databases (3NF) with proper primary keys (PK) and foreign keys (FK). Uses intelligent heuristics to detect vertices and edges - no manual schema definition needed! Perfect for migrating relational data to graph databases.
  6. 🔗 RDF / Turtle Ingestion with Explicit Resource Mapping - Infer graph schemas from OWL ontologies and ingest RDF data using explicit SparqlConnector resource mapping. Supports local Turtle files and remote SPARQL endpoints. Perfect for knowledge graph pipelines built on semantic web standards.
  7. Polymorphic Objects and Relations — Route polymorphic entities and dynamic relations using two vertex_router steps and a dynamic edge step. One objects table (Person, Vehicle, Institution) and one relations table (EMPLOYED_BY, OWNS, FUNDS, etc.) map to a rich graph with type discriminators and relation_map.
  8. Multi-edge properties with filters and dress transforms — Ticker-style CSV to Neo4j with vertex filters, rich relationship payload, and dress-scoped transforms on metric name/value pairs.
  9. Explicit connector_connection Proxy Wiring — Show how manifest proxy labels (conn_proxy) are resolved at runtime into real DB configs via ConnectionProvider.
  10. TigerGraph bulk load and S3 staging — Opt-in CSV staging and native LOADING JOB, with bindings.staging_proxy and S3GeneralizedConnConfig (MinIO, AWS S3, or other S3-compatible endpoints).
  11. Flat-row dynamic edges with vertex_router — Each CSV row encodes a complete (source, target, relation) tuple. Two vertex_router steps accumulate endpoint vertices into named role slots; a dynamic edge step resolves types from those slots.
  12. Vertex roles and multi-intent edges — One flat row, three same-type vertices (self / parent / child), two edge types. Uses role on vertex steps for named accumulator slots and links on the edge step to emit multiple relationships in one pipeline step.