redis-core
Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
Works with
---
name: redis-core
description: Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
license: MIT
---
# Redis Core
Foundational guidance for modeling data in Redis. Covers data-type selection and key-name conventions — the two decisions that most directly drive memory, performance, and maintainability.
## When to apply
- Caching objects, sessions, or per-user state.
- Counters, leaderboards, recent-items lists, unique-membership sets.
- Reviewing or refactoring Redis key names.
- Deciding between a Redis Hash and a JSON document for an entity.
## 1. Choose the right data structure
Pick the type that matches the *access pattern*, not just the shape of the data.
| Use case | Recommended type | Why |
|---|---|---|
| Simple values, counters | String | Atomic `INCR`/`DECR`, `SET`/`GET` |
| Object with independently updated fields | Hash | Per-field reads/writes, no whole-object rewrite |
| Queue, recent-N items | List | O(1) push/pop at ends |
| Unique items, membership checks | Set | O(1) `SADD`/`SISMEMBER`/`SCARD` |
| Rankings, score-based ranges | Sorted Set | Score-ordered; `ZADD`/`ZRANGE`/`ZRANK` |
| Nested / hierarchical data | JSON | Path-level updates, nested arrays, RQE indexing |
| Event log, fan-out messaging | Stream | Persistent, consumer groups |
| Vector similarity | Vector Set | Native vector storage with HNSW |
**Common anti-pattern:** stuffing a flat object into a serialized string. Updating one field means fetch + parse + mutate + rewrite. Use a Hash instead.
See [references/choose-data-structure.md](references/choose-data-structure.md) for full rationale and Python/Java examples.
## 2. Use consistent key names
Use `colon-separated` segments with a stable hierarchy:
```
{entity}:{id}:{attribute}
user:1001:profile
user:1001:settings
order:2024:items
session:abc123
article:987:likes
game:space-invaders:leaderboard
```
Rules of thumb:
- **Lowercase, colon-separated.** No spaces, no mixed casing (`User_1001_Profile` is bad).
- **Keep keys short but readable** — keys live in memory and appear in every command.
- **Don't use full URLs or long strings as keys.** Extract a short identifier, or use a hash digest of the URL.
- **Prefix for multi-tenancy** (`tenant:42:user:7:cart`) so scans and ACLs can target a tenant cleanly.
- **Be consistent.** Pick one convention per service and apply it across all keys.
See [references/key-naming.md](references/key-naming.md) for cleanup examples and edge cases.
## References
- [Redis: Choosing the right data type](https://redis.io/docs/latest/develop/data-types/compare-data-types/)
- [Redis: Keys](https://redis.io/docs/latest/develop/use/keyspace/)More Database skills
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