Data Management with Core Data

Abstract

Working with structured data has long been a complex topic with many facets to consider, such as the structure of data in memory vs. its structure in permanent storage, the means to convert between the two, and the best way to deal with potentially infinite data sets without jeopardizing performance at any level. There are many different approaches to solving this problem; data formats such as XML and JSON play their part, as do large-scale storage engines such as SQL databases, key-value stores like Tokyo Cabinet, and document stores like CouchDB. All have their own representations, APIs, and their own sets of features and limitations. Choosing between them is often a decision that is hard to change later, once you’ve committed thousands of lines of code to a particular paradigm.