> ## 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.

# Key-Value Stores

> Worlds vs Key-Value Stores: RDF fact ledger vs high-speed key-value caches.

## At a glance

|              | Worlds                                                | Key-Value Stores ([Redis](https://redis.io/docs/), [Dragonfly](https://www.dragonflydb.io/docs/), [Memcached](https://memcached.org/)) |
| :----------- | :---------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------- |
| Primary role | Authoritative RDF fact ledger & SPARQL context engine | In-memory key-value caching & data structures                                                                                          |
| Data model   | RDF triples/quads in an append-only graph ledger      | Opaque byte arrays, strings, hashes, lists, sets                                                                                       |
| Querying     | SPARQL graph traversal, full-text, & vector fusion    | Direct key lookup, range queries, & pub/sub commands                                                                                   |
| Persistence  | Permanent append-only ledger on edge/cloud backends   | In-memory with optional asynchronous disk snapshots                                                                                    |
| Purpose      | Verifiable agent context engine                       | Low-latency caching, session storage, & rate limiting                                                                                  |

## Overlap and shared capabilities

Both Worlds and key-value stores prioritize retrieval performance and simple
developer interfaces. Key-value stores like Deno KV can even serve as a
underlying storage substrate for Worlds adapters.

The difference:

* Key-value stores treat values as opaque blobs accessible primarily by key.
  They do not parse or index relationship graphs between stored items.
* Worlds models data as explicit RDF quads, indexing subjects, predicates, and
  objects so agents can query connections between facts.

## When Worlds fits

* You need graph relationship traversal (SPARQL) across stored facts.
* You require verified context retrieval combining vector embeddings with graph
  filters.
* You need permanent quad provenance and change ledgers for AI agent operations.

## When Key-Value Stores fit

* You need ultra-low latency sub-millisecond caching for hot data.
* You are managing ephemeral user sessions, rate limits, or pub/sub queues.
* You only need direct key-to-value lookups without semantic relationships.