db-comparison
Database selection — strengths and use-case mapping by type.
SKILL.mdskills/database/db-comparison/SKILL.md
GitHubRelational
| Database | Strengths | Watch out for |
|---|---|---|
| PostgreSQL | Full SQL, JSONB, extensions, ACID | Config tuning needed for performance |
| MySQL / MariaDB | Wide support, simple ops | Less feature-rich than Postgres |
| SQL Server | Enterprise features, .NET integration | Licensing cost |
| SQLite | Zero config, embedded | Not for concurrent writes |
Document
| Database | Strengths | Watch out for |
|---|---|---|
| MongoDB | Flexible schema, horizontal scale | No joins, eventual consistency tradeoffs |
| Firestore | Real-time, serverless-friendly | Query limitations, cost at scale |
| Cosmos DB | Multi-model, global distribution | Complex pricing, learning curve |
Key-Value / Cache
| Database | Use case |
|---|---|
| Redis | Cache, sessions, queues, pub/sub, leaderboards |
| Memcached | Simple distributed cache |
| ElastiCache / Memorystore / Azure Cache | Managed Redis/Memcached |
Column-Family
| Database | Use case |
|---|---|
| Cassandra / Keyspaces | High-write, time-series, distributed |
| Bigtable | Analytics, IoT, wide-column |
Vector / AI
| Database | Use case |
|---|---|
| pgvector (PostgreSQL ext.) | Semantic search, embeddings, RAG pipelines — load skills/architecture/llm-integration/SKILL.md |
| Dedicated vector DBs | Pinecone, Weaviate, Qdrant — when Postgres can't scale the vector workload |
Managed Cloud (defer to cloud specialists when infra decisions needed)
- AWS: RDS, Aurora, DynamoDB, ElastiCache, DocumentDB, Redshift
- GCP: Cloud SQL, Spanner, Firestore, Bigtable, Memorystore, BigQuery
- Azure: Azure SQL, Cosmos DB, Cache for Redis, Synapse Analytics