MongoDB Documentation, Release 3.0.4 4.1.4 Data Use and Performance 4.1.5 Additional Resources 4.2 Data Modeling Concepts $^{1}$https://www.mongodb.com/blog/post/thinking-documents-part-1?jmp=docs 145 4.2. Data Modeling Concepts When designing a data model, consider how applications will use your database. For instance, if your application only uses recently inserted documents, consider using Capped Collections (page 209). Or if your application needs are mainly read operations to a collection, adding indexes to support common queries can improve performance. See Operational Factors and Data Models (page 148) for more information on these and other operational considera- tions that affect data model designs. Consider the following aspects of data modeling in MongoDB: For a general introduction to data modeling in MongoDB, see the Data Modeling Introduction (page 143). For example data models, see Data Modeling Examples and Patterns (page 151). • Thinking in Documents Part 1 (Blog Post) 1 Data Model Design (page 146) Presents the different strategies that you can choose from when determining your data model, their strengths and their weaknesses. Operational Factors and Data Models (page 148) Details features you should keep in mind when designing your data model, such as lifecycle management, indexing, horizontal scalability, and document growth. GridFS (page 150) GridFS is a specification for storing documents that exceeds the BSON -document size limit of 16MB.