Message Queues - Wazoo Docs

At a glance

	Worlds	Message Queues (Kafka, RabbitMQ, SQS, NATS)
Primary role	Authoritative RDF fact ledger & SPARQL context engine	Asynchronous message broker & event streaming bus
Data model	RDF triples/quads in an append-only graph ledger	Sequential message topics, queues, & event logs
Retrieval	SPARQL graph queries, full-text, & vector fusion	Consumer log offsets & push/pull queue delivery
Core purpose	Verifiable agent memory & context retrieval	Decoupling microservices & streaming event processing
Querying	Complex multi-hop graph queries & vector search	Topic streaming & consumer group offset tracking

Overlap and shared capabilities

Both Worlds and streaming event logs (like Kafka) use immutable, append-only logs as core storage primitives. Both allow tracking temporal event changes over time. The difference:

Message queues stream events between microservices. They prioritize throughput and queue delivery, but do not support indexing or querying graph relationships across historical messages.
Worlds indexes assertions into an RDF knowledge graph, enabling agents to run SPARQL queries and hybrid vector searches across historical facts.

When Worlds fits

You need to query the current state and provenance of connected facts.
You require hybrid vector + SPARQL graph search for AI agent context retrieval.
You are storing durable knowledge rather than transient inter-service messages.

When Message Queues fit

You need asynchronous task queueing or pub/sub broadcasting between services.
You are streaming high-volume raw telemetry or event logs.
You need microservice decoupling and guaranteed message delivery semantics.