vector-database-ops
Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.
npx skills add majiayu000/claude-skill-registry --skill vector-database-ops --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Vector Database Operations Run production vector databases for AI-powered search, RAG, and recommendation systems. ## When to Use This Skill Use this skill when: - Setting up a vector database for a RAG or semantic search application - Choosing between Qdrant, Weaviate, pgvector, or Pinecone - Managing collections, indexes, and data migrations - Optimizing query performance and indexing for production loads - Implementing multi-tenant vector search with namespace isolation ## Vector Database Comparison | Database | Best For | Hosting | Filtering | Scale | |----------|----------|---------|-----------|-------| | **Qdrant** | High-performance, rich filtering, self-hosted | Self / Cloud | Excellent | Very High | | **Weaviate** | Schema-first, hybrid search, multi-modal | Self / Cloud | Good | High | | **pgvector** | Already on Postgres, simple use cases | Self | Good | Medium | | **Pinecone** | Zero-ops managed, serverless | Managed only | Good | Very High | | **Chroma** | Local dev, prototyping | Self only | Basic | Low-Medium | ## Qdrant — Production Deployment ```bash # Docker (single node) docker run -d \ --name qdrant \ -p 6333:6333 \ -p 6334:6334 \ -v $(pwd)/qdrant-data:/qdrant
- When to Use This Skill
- Vector Database Comparison
- Qdrant — Production Deployment
- Qdrant Collection Management
- Qdrant Filtered Search
- pgvector — PostgreSQL Extension
- Weaviate Deployment
- Backup and Restore
- Performance Tuning
- Common Issues
- Best Practices
- Related Skills
Docker (single node) docker run -d \ With custom config Deploy pgvector via Docker Qdrant — snapshot backup curl -X POST "http://localhost:6333/collections/documents/snapshots" Download snapshot curl -O "http://localhost:6333/collections/documents/snapshots/documents-snapshot.snapshot" Restore curl -X POST "http://localhost:6333/collections/documents/snapshots/recover" \
What does the vector-database-ops skill do?
Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill vector-database-ops --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.