Examples Overview¶

This section contains complete, runnable examples for every query language and use case supported by IndentiaDB. All examples are tested against a running IndentiaDB instance and include the expected output.

Example Categories¶

SurrealQL Examples¶

25 examples covering all SurrealQL capabilities:

• Relational / SQL — math aggregates, string functions, array functions, date/time, conditional expressions, subqueries, pagination, GROUP BY
• NoSQL / Document — nested CRUD, array manipulation, SCHEMAFULL validation, SCHEMALESS flexibility, record links, UPSERT/MERGE, DELETE patterns, type checking
• Graph Edges — RELATE, outgoing traversal (->), incoming traversal (<-), bidirectional (<->), edge property queries, multi-hop patterns
• Advanced — transactions (BEGIN/COMMIT/CANCEL), DEFINE EVENT triggers, indexes and unique constraints

RDF & SPARQL Examples¶

25 examples covering the native RDF triple store and SPARQL 1.2 engine:

• Basics — insert and query typed triples, named graphs, blank nodes, literal datatypes, language-tagged literals, SPO pattern combinations, triple deletion, class hierarchies
• SPARQL Queries — SELECT with FILTER and OPTIONAL, aggregates (COUNT, GROUP BY, HAVING), CONSTRUCT, ASK, property paths, SPARQL UPDATE
• Advanced RDF — RDF-star provenance annotations, federated queries (SERVICE), RDFS inference, OWL reasoning (sameAs, inverseOf, symmetricProperty, transitiveProperty), hybrid SPARQL() in SurrealQL
• Real-World Use Cases — organization ontology, supply chain traceability, compliance & regulatory, IT infrastructure (CMDB), medical ontology, research publications

LPG Graph Examples¶

20 examples covering the Labeled Property Graph engine:

• LPG from RDF — label scan, traversal with property filter, bidirectional traversal, multi-hop depth, shortest path, PageRank, connected components, neighbor count
• LPG from Documents — document table projection, incremental RDF delta
• Multi-Model LPG — RDF-to-LPG projection, PageRank via CSR, combined document + RDF, incremental updates
• ACL Integration — admin visibility, deny policy, per-IRI permission cache, graph-level default permission
• CSR Algorithms — PageRank convergence, connected components with label filter

Enterprise Search Examples¶

25 examples covering all search modalities:

• Full-Text Search (BM25) — basic search, multi-field, highlighting, fuzzy/stemming, phrase search, boolean filters, faceted aggregation
• Vector / RAG — cosine similarity store, KNN with Euclidean distance, hybrid text + vector, RAG chunk-and-retrieve, context window assembly, metadata-filtered search, chunk deduplication
• AI Agent Patterns — tool registry, conversation memory, knowledge extraction, task planning (DAG), observation log, chain-of-thought reasoning, multi-source knowledge fusion
• Enterprise Patterns — access-controlled search, search audit trail, document lifecycle, cross-lingual search

Live Data & Agent Examples¶

25 examples covering reactive and real-time patterns:

• DEFINE EVENT Triggers — audit log on CREATE, field change tracking on UPDATE, archive on DELETE, cascade status updates, conditional events, multi-table activity feed
• Change Tracking — timestamp-based polling, optimistic locking, before/after changelog, cursor-based pagination, snapshot differentials, changelog compaction
• AI Agent Real-Time — inbox pattern, FIFO task queue, pub/sub channels, agent state machine, collaborative editing, heartbeat monitoring, event sourcing
• Reactive Patterns — materialized views, notification system, cache invalidation, data pipeline, threshold alerts, knowledge graph sync

Multi-Model Examples¶

5 examples demonstrating how all four data models work together in a single IndentiaDB instance:

1. Relational / SQL style — typed tables, aggregates, subqueries
2. NoSQL / Document — schemaless tables with nested objects and record links
3. Graph RDF — triples with ontology and instance data
4. Graph LPG — traversals, shortest path, PageRank, and connected components over RDF data
5. Combined transaction — a single dataset that spans document tables, RDF triples, and LPG projections with incremental updates

Use Cases: Enterprise Search, RAG & AI Agents¶

15 examples demonstrating real-world patterns that combine RDF knowledge graphs with search, retrieval, and agent architectures:

• Enterprise Search with Knowledge Graphs — knowledge-enriched document search, faceted search from ontology, entity-linked search results, multi-tenant secure knowledge base, regulatory search with compliance graph
• RAG (Retrieval-Augmented Generation) — RAG with RDF knowledge context, graph-guided chunk retrieval, multi-hop fact retrieval, provenance tracking with RDF-star, hybrid RAG (vector + BM25 + knowledge graph)
• AI Agent Patterns — agent knowledge base with RDF ontology, tool selection via capability graph, multi-agent collaboration with shared knowledge graph, episodic + semantic agent memory, agent reasoning with graph traversal

Running the Examples¶

All examples require a running IndentiaDB instance. Start one quickly with Docker:

docker run -d \
  --name indentiadb \
  -p 7001:7001 \
  -p 9200:9200 \
  -e SURREAL_USER=root \
  -e SURREAL_PASS=changeme \
  ghcr.io/indentiaplatform/indentiadb-trial:latest

Execute SurrealQL examples via the HTTP API:

curl -u root:changeme \
  -X POST http://localhost:7001/sql \
  -H "Content-Type: application/json" \
  -d '{"query": "SELECT * FROM employee ORDER BY name"}'

Execute SPARQL examples:

curl -u root:changeme \
  -X POST http://localhost:7001/sparql \
  -H "Content-Type: application/sparql-query" \
  -H "Accept: application/sparql-results+json" \
  -d 'SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10'