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Can I optimize a Core Data query when searching for matching words in a text? (This question also pertains to the wisdom of custom SQL versus Core Data on an iPhone.) I'm working on a new (iPhone) app that is a handheld reference tool for a scientific database. The main interface is a standard searchable table view and I want as-you-type response as the user types new words. Words matches must be prefixes of words in the text. The text is composed of 100,000s of words. In my prototype I coded SQL directly. I created a separate "words" table containing every word in the text fields of the main entity. I indexed words and performed searches along the lines of SELECT id, * FROM textTable JOIN (SELECT DISTINCT textTableId FROM words WHERE word BETWEEN 'foo' AND 'fooz' ) ON id=textTableId LIMIT 50 This runs very fast. Using an IN would probably work just as well, i.e. SELECT * FROM textTable WHERE id IN (SELECT textTableId FROM words WHERE word BETWEEN 'foo' AND 'fooz' ) LIMIT 50 The LIMIT is crucial and allows me to display results quickly. I notify the user that there are too many to display if the limit is reached. This is kludgy. I've spent the last several days pondering the advantages of moving to Core Data, but I worry about the lack of control in the schema, indexing, and querying for an important query. Theoretically an NSPredicate of textField MATCHES '.*\bfoo.*' would just work, but I'm sure it will be slow. This sort of text search seems so common that I wonder what is the usual attack? Would you create a words entity as I did above and use a predicate of "word BEGINSWITH 'foo'"? Will that work as fast as my prototype? Will Core Data automatically create the right indexes? I can't find any explicit means of advising the persistent store about indexes. I see some nice advantages of Core

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