Exasol: early design choices
Making good choices when designing a data model is crucial for optimal performance, so it pays to get it right from the start.
Many database problems can be traced back to early design choices that didn't seem critical at the time. Mixing multiple values in one column, loosely defined entities, or schemas that don't reflect how the data is actually used: it all creates friction later, especially as systems grow.
According to Exasol, good database design is less about technology and more about the fundamentals. The principles are well known, but easy to overlook when speed is the priority:
- defining entities and relationships clearly
- keeping data atomic
- normalising deliberately (and denormalising only for a clear reason)
- enforcing integrity through keys and constraints
- designing with actual query patterns in mind
- separating transactional and analytical workloads
None of this is new, but it's often where things start to break. Would you like your data model reviewed? Read more about our view on data architecture.