key-value

## What I do - Design key-value schemas and data models - Implement caching strategies and policies - Optimize for low-latency access patterns - Work with distributed hash tables - Handle data partitioning and replication ## When to use me When building high-performance applications requiring fast lookups, caching layers, session stores, or distributed caching systems. ## Key Concepts ### Data Modeling - Key design patterns (natural keys, composite keys) - Value serialization (JSON, protobuf, msgpack) - Time-to-live (TTL) and expiration - Namespace and prefix patterns ### Caching Strategies - Cache-aside (lazy loading) - Write-through caching - Write-back caching - Cache invalidation patterns - Bloom filters for cache miss reduction ### Distributed Key-Value - Consistent hashing - Data partitioning (sharding) - Replication strategies - CAP theorem trade-offs - CRDTs for conflict resolution ### Performance Optimization - In-memory vs disk-backed stores - Data structure choices (B-trees, LSM trees, hash tables) - Connection pooling - Batch operations - Compression ## Common Use Cases - Session storage - Caching layer - Configuration stores - Rate limiting - Leader election - Distributed locks ## Tools & Technologies - Redis, Memcached - etcd, Consul - DynamoDB, Cassandra - Riak, CockroachDB