Choosing Your Vector Database

A standard SQL database is built for numbers and strings. A Vector Database is built specifically to store and search billions of multi-dimensional vectors in milliseconds.

1. Azure AI Search (Managed)

The choice for .NET Enterprise. It combines classic full-text search with vector capabilities. Pros: Built-in security (RBAC), easy integration with Azure OpenAI, and handles complex document types like PDF and Word automatically via "Indexers."

2. Pinecone (SAAS)

The industry leader for "Speed and Ease of Use." It is completely Serverless. You just push your vectors via an API and don't worry about infra. Perfect for startups and fast scaling.

3. Milvus / Qdrant (Self-Hosted)

If you have strict privacy requirements and can't use the cloud, these are the kings of the open-source world. They are built for extreme high performance and can handle trillions of vectors on your own hardware.

4. Interview Mastery

Q: "Can I just use SQL Server or Postgres for Vectors?"

Architect Answer: "Yes, for small to medium datasets. Postgres has the **pgvector** extension, and SQL Server is adding native vector support. For <100,000 documents, using your existing DB is cheaper and simpler. However, once you reach millions of documents, specialized Vector DBs use advanced algorithms like **HNSW** (Hierarchical Navigable Small World) that are 10-100x faster than traditional DB indexes for similarity search."