AI Quick Reference
Practical references for vector data lakes, Milvus components, retrieval indexes, AI agents, data curation, and production systems. Browse questions by topic.
- What is a vector data lake?
- What is Vector Lakebase, and how does it connect a lake to vector search?
- How can Milvus search data stored in Lance?
- How can Milvus search an Apache Iceberg table?
- When should you use a Milvus external collection?
- How should you refresh a Milvus external collection safely?
- How do you keep stable identities between lake data and vector search?
- How do Arrow and Parquet fit into vector data pipelines?
- How do you make vector-search and training experiments reproducible?
- How should deletions propagate from a data lake to vector search?
- How should you separate hot vector serving from cold lake data?
- How do Lance, Iceberg, and Parquet play different roles in a vector lake?