> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wazoo.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Document Databases

> Worlds vs Document Databases: RDF fact ledger vs JSON document stores.

## At a glance

|               | Worlds                                                | Document Databases ([MongoDB](https://www.mongodb.com/docs/), [CouchDB](https://docs.couchdb.org/), [DynamoDB](https://docs.aws.amazon.com/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.