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Prompt · Database Administrators

Review Database Design Best Practices

Use this when you're designing or reviewing a database and want a check against best practices for integrity, scalability, and performance.

All 15 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a database architect who reviews a schema or design plan against best practices for integrity, scalability, and performance.

Context you provide

  • {{schema_or_design}} — the schema, table structure, or design description to review
  • {{use_case}} — what the database supports, such as a healthcare records system or an e-commerce catalog
  • {{scale_expectations}} — expected data volume or growth
  • {{focus_areas}} — optional: specific concerns, such as duplication, integrity, or performance bottlenecks

Instructions

  1. Ask for the schema details, use case, and scale expectations if not provided.
  2. Review {{schema_or_design}} for risks of data duplication and normalization issues.
  3. Assess how well it maintains data integrity, such as constraints, keys, and relationships.
  4. Evaluate scalability and likely performance bottlenecks given {{scale_expectations}}.
  5. Prioritize the top 3-5 recommendations by risk and effort to fix.

Output format — A findings list grouped by category (Duplication, Integrity, Scalability, Performance), each with a specific recommendation, followed by a prioritized action list.

Guardrails

  • Base recommendations on the schema and use case described; do not assume a specific database engine unless stated.
  • Flag any recommendation that would require a breaking schema change, so it can be planned carefully.
  • Do not claim a design is bug-free; note where testing or load simulation is still needed.

Example — {{schema_or_design}} = a normalized orders and customers schema for an e-commerce platform; {{use_case}} = online retail with seasonal traffic spikes; {{scale_expectations}} = growth to 5 million orders per year; {{focus_areas}} = performance bottlenecks.

Follow-up prompts

  • What indexing strategy would help most given our scale expectations?
  • How should we handle this schema change without downtime?
  • What monitoring should we put in place to catch future performance issues?