Designing Data-Intensive Applications [Book Highlights]

[Part I : Chapter II]

Data Models and Query Languages

• The goal of the relational model was to hide that implementation detail behind a cleaner interface.
• Object-relational mapping (ORM) frameworks like ActiveRecord and Hibernate reduce the amount of boilerplate code required for this translation layer, but they can’t completely hide the differences between the two models.
• In a relational database, the query optimizer automatically decides which parts of the query to execute in which order, and which indexes to use.
• Schema flexibility in the document model Most document databases, and the JSON support in relational databases, do not enforce any schema on the data in documents.
• If the data in your application has a document-like structure (i.e., a tree of one-to many relationships, where typically the entire tree is loaded at once), then it’s probably a good idea to use a document model. The relational technique of shredding— splitting a document-like structure into multiple tables can lead to cumbersome schemas and unnecessarily complicated application code.
• Schema-on-read is similar to dynamic (runtime) type checking in programming languages, whereas schema-on-write is similar to static (compile-time) type checking.
• If your application often needs to access the entire document, there is a performance advantage to this storage locality.
• The locality advantage only applies if you need large parts of the document at the same time.
• It seems that relational and document databases are becoming more similar over time, and that is a good thing