Document Databases - Wazoo Docs

At a glance

	Worlds	Document Databases (MongoDB, CouchDB, DynamoDB)
Primary role	Authoritative RDF fact ledger & SPARQL context engine	Hierarchical JSON document storage & retrieval
Data model	RDF triples/quads in an append-only graph ledger	Semi-structured JSON/BSON documents
Relationships	Explicit first-class graph edges with SPARQL queries	Embedded subdocuments or manual document references
Retrieval	SPARQL graph queries, full-text, & vector fusion	Field queries, aggregation pipelines, & key lookups
Provenance	Immutable quad provenance & assertion ledger	Document revision histories or custom fields

Overlap and shared capabilities

Both Worlds and document databases offer schema flexibility, allowing data structures to evolve without strict table migrations. Both support storing semi-structured metadata alongside content. The difference:

Document databases nest data hierarchically within document boundaries. Cross-document relationships require manual references or expensive lookup joins.
Worlds connects atomic facts into a unified RDF graph. Subject-predicate-object triples allow agents to query relationships across entity boundaries effortlessly.

When Worlds fits

You need interconnected knowledge retrieval across multiple domain entities.
You require SPARQL graph queries and quad provenance tracking for verifiable agent responses.
You want hybrid search across RDF graphs, full-text indexes, and vector embeddings.

When Document Databases fit

Your application data is naturally hierarchical and self-contained (e.g. user profiles, blog posts).
You require rapid single-key JSON document retrieval.
You are building general document storage workflows.