Back to Module 1.8: Vector DatabasesComing Soon
AI Lesson & Submodule
Vector DB Interview Guide
Prepare for system architecture interviews focused on vector databases.
Why This Matters
Architects must justify database software choices based on security, hosting models, and cost constraints.
What You Will Learn
- •Compare Pinecone vs Chroma
- •Detail HNSW configurations
- •Explain hybrid scoring
Concepts Covered
Serverless vector backendsSelf-hosted Chroma/FAISS setupsGraph index structures
Mapped Foundation Project: Semantic Product Search
Search workspace loading catalog inventories into vector databases, supporting dense vector lookups and metadata query filtering.
Architecture Preview
Search gateway loading documents into vector databases, querying them on keys, and merging results streams.
Search Query InputEmbeddings TransformerVector DB Index
Tech Stack Planned
ReactTypeScriptTailwind CSS
GitHub: Coming SoonLive Demo: Coming Soon
Coming SoonTechnical Interview Value
- ?Compare self-hosting Chroma/FAISS indexes against deploying to serverless Pinecone engines