Understanding NoSQL data modeling helps improve application performance, developer productivity, and reduces overall costs.
NoSQL document databases like MongoDB store data in BSON documents grouped into collections with flexible schemas, unlike rigid SQL tables.
Model one-to-many relationships using either embedding to store related data within a single document or referencing to link separate documents via IDs.
Use embedding for one-to-few relationships and referencing for one-to-zillions relationships to avoid oversized documents and performance issues.
Decide whether to embed or reference by determining if the related data constitutes a separate logical unit that needs to be queried independently.
Combine referencing with embedding minimal, frequently needed data to optimize critical queries and avoid multiple lookups.
Embrace necessary data duplication for historical accuracy and manage staleness by using batch updates with MongoDB Change Streams.
Effective data modeling is driven by application use cases, relationship cardinality, and the identification of critical queries.
Sensory-Minds GmbH
Offenbach am Main, Germany
Hubert Burda Media
München, Germany
fulfillmenttools
Köln, Germany
44:51Stanimira Vlaeva
47:16Maxime Beugnet
28:13Erick Wendel
31:08Hartmut Armbruster
51:04Noam Honig
24:22Jürgen Pilz
32:56Laurie Voss
37:21Mario Meir-Huber
Jobs that call for the skills explored in this talk.
Antal International
Barcelona, Spain
Sept Lieues
Paris, France
Da Vinci Engineering GmbH
Stuttgart, Germany
Antal International
Municipality of Valencia, Spain
Percona
Antal International
Municipality of Madrid, Spain