Three things to know about document database modelling: part 1

When modeling a document database, it's essential to consider the trade-offs between queryability and data integrity. Answering questions you know you'll ask upfront is crucial, as this allows for pre-computing answers that can be pulled from the database in a single lookup. This approach differs from relational databases, where queries are often more complex and CPU-intensive. By embedding data for convenience and referring to it for integrity, developers can optimize their document database models for performance and scalability. The key is to balance queryability with data consistency, ensuring that updates are universal and easy to query. In a production system, generating multiple pre-computed answers can improve user experience and reduce lag, while also making it easier to distribute data across a cluster.

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