vector-databases
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization. Use when choosing vector stores, designing semantic search, or optimizing similarity search performance.
npx skills add majiayu000/claude-skill-registry --skill vector-databases --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 Databases ## When to Use This Skill Use this skill when: - Choosing between vector database options - Designing semantic/similarity search systems - Optimizing vector search performance - Understanding ANN algorithm trade-offs - Scaling vector search infrastructure - Implementing hybrid search (vectors + filters) **Keywords:** vector database, embeddings, vector search, similarity search, ANN, approximate nearest neighbor, HNSW, IVF, FAISS, Pinecone, Weaviate, Milvus, Qdrant, Chroma, pgvector, cosine similarity, semantic search ## Vector Database Comparison ### Managed Services | Database | Strengths | Limitations | Best For | | -------- | --------- | ----------- | -------- | | **Pinecone** | Fully managed, easy scaling, enterprise | Vendor lock-in, cost at scale | Enterprise production | | **Weaviate Cloud** | GraphQL, hybrid search, modules | Complexity | Knowledge graphs | | **Zilliz Cloud** | Milvus-based, high performance | Learning curve | High-scale production | | **MongoDB Atlas Vector** | Existing MongoDB users | Newer feature | MongoDB shops | | **Elastic Vector** | Existing Elastic stack | Resource heavy | Search platforms | ### Self-Hosted Options | Database |
- When to Use This Skill
- Vector Database Comparison
- Managed Services
- Self-Hosted Options
- Selection Decision Tree
- ANN Algorithms
- Algorithm Overview
- HNSW (Hierarchical Navigable Small World)
- IVF (Inverted File Index)
- IVF-PQ (Product Quantization)
- Algorithm Comparison
- When to Use Which
- Distance Metrics
- Common Metrics
What does the vector-databases skill do?
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization. Use when choosing vector stores, designing semantic search, or optimizing similarity search performance.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill vector-databases --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.