Went through the usual suspects: B-tree, hash, composite, partial.
Start by categorizing indexes based on their structure (e.g., B-tree, hash) and their logical usage (e.g., primary, secondary, composite). Then, briefly explain each type's purpose and trade-offs, focusing on how they impact query performance and storage. Conclude by mentioning that the choice depends on the workload and data characteristics.
Pro tip: Demonstrate depth by discussing not just the types but also when to use each, and mention that over-indexing can degrade write performance. This shows you understand the practical trade-offs in database design.
Begin by classifying indexes based on their underlying data structure, such as B-tree, hash, bitmap, and specialized types like GiST or GIN.
Explain indexes based on their role: primary key, unique, composite, covering, and full-text indexes.
For each type, provide a one-sentence description of its purpose and a key characteristic (e.g., B-tree for range queries, hash for equality).
Highlight the trade-offs: faster reads vs. slower writes, increased storage, and maintenance overhead.
Summarize that the choice depends on query patterns, data volume, and write frequency, showing a balanced understanding.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.