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CRUD Lies: Hidden Pitfalls of Simple Updates
- CRUD (Create, Read, Update, Delete) operations might seem simple, but they can hide pitfalls like lost data from race conditions, lack of audit trails for critical changes, and hidden coupling between features.
- The illusion of atomicity with UPDATE operations can lead to lost updates due to race conditions.
- Solutions include using database locks or optimistic concurrency to prevent lost updates.
- The vanishing history problem arises when apps lack proper logging of data changes, causing issues in tracking changes.
- Solutions involve implementing event-driven sidecars or Change Data Capture (CDC) tools to track database changes effectively.
- The dependency time bomb problem occurs when a seemingly simple column update triggers unexpected side effects due to callbacks.
- Solutions include using explicit workflows or event-driven decoupling to manage callbacks more effectively.
- The phantom update problem arises when UPDATE operations affect more columns than intended, leading to data discrepancies.
- Solutions involve using partial updates or strict column lists to control which columns are updated.
- Using CRUD is suitable for scenarios like simple admin dashboards, internal tools without audit needs, and early-stage prototypes where 'last write wins' is acceptable.
- It is recommended to add auditing, replace callbacks with services, and measure impact before fully embracing event-driven architectures.
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