Question

I have a choice of creating three tables with identical structure but different content or one table with all of the data and one additional column that distinguishes the data. Each table will have about 10,000 rows in it, and it will be used exclusively for looking up data. The key design criteria is speed of lookup, so which is faster: three tables with 10K rows each or one table with 30K rows, or is there no substantive difference? Note: all columns that will be used as query parameters will have indices.

Answer 1

There should be no substantial difference between 10k or 30k rows in any modern RDBMS in terms of lookup time. In any case not enough difference to warrant the de-normalization. Indexed qualifier column is a common approach for such a design.

The only time you may consider de-normalizing if your update pattern affects a limited set of data that you can put in a “short” table (say, today’s messages in social network) with few(er) indexes for fast inserts/updates and there is a background process transferring the stabilized updates to a large, fully indexed table. The case were you really win during write operations will be a dramatic one though, with very particular and unfortunate requirements. RDBMS engines are sophisticated enough to handle most of the simple scenarios in very efficient way. 30k or rows does not sound like a candidate.

If still in doubt, it is very easy to write a test to check on your particular database / system setup. I think if you post your findings here with real data, it will be a useful info for everyone in your steps.