Your application's query patterns, not normalization rules, should drive your data model.
#1about 3 minutes
Why data modeling matters for front-end developers
A good data model improves application performance, developer productivity, and reduces overall development costs.
#2about 7 minutes
Understanding document databases and flexible schemas
NoSQL document databases like MongoDB use collections of BSON documents with flexible schemas, unlike the rigid tables of SQL.
#3about 6 minutes
Modeling data relationships with embedding and referencing
One-to-many relationships can be modeled by either embedding related data within a single document or by referencing it using IDs.
#4about 9 minutes
Deciding when to embed or reference data
Use embedding for one-to-few relationships and referencing for one-to-zillions, while considering if entities are separate logical units for one-to-many cases.
#5about 6 minutes
Optimizing queries with the extended reference pattern
Combine referencing with embedding of frequently accessed fields to reduce queries while avoiding overly large documents and data duplication.
#6about 5 minutes
Handling data duplication and staleness effectively
Accept duplication for historical data and manage necessary updates for stale data using batch operations triggered by change streams.
#7about 9 minutes
Core principles for successful NoSQL data modeling
Effective data modeling is driven by application use cases, requiring identification of logical units, relationships, and critical queries.
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