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    <p>It depends on a lot of factors - but most crucially:</p> <ul> <li>complexity of calculations (prefer doing complex crunching on an app-server, since that scales <em>out</em>; rather than a db server, which scales <em>up</em>)</li> <li>volume of data (if you need to access/aggregate a lot of data, doing it at the db server will save bandwidth, and disk io if the aggregates can be done inside indexes)</li> <li>convenience (sql is not the best language for complex work - especially not great for procedural work, but very good for set-based work; lousy error-handling, though)</li> </ul> <p>As always, if you <em>do</em> bring the data back to the app-server, minimising the columns and rows will be to your advantage. Making sure the query is tuned and appropriately indexed will help either scenario.</p> <p>Re your note:</p> <blockquote> <p>and then loop through the records </p> </blockquote> <p><em>Looping</em> through records is almost always the wrong thing to do in sql - writing a set-based operation is preferred.</p> <p><em>As a general rule</em>, I prefer to keep the database's job to a minimum "store this data, fetch this data" - however, there are always examples of scenarios where an elegant query at the server can save a lot of bandwidth.</p> <p>Also consider: if this is computationally expensive, can it be cached somewhere?</p> <p>If you want an <em>accurate</em> "which is better"; code it both ways and compare it (noting that a first draft of either is likely not 100% tuned). But factor in typical usage to that: if, in reality, it is being called 5 times (separately) at once, then simulate that: don't compare just a single "1 of these vs 1 of those".</p>
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    1. POWhat are the pros and cons of performing calculations in sql vs. in your application
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    1. USMarc Gravell
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    1. CO+1 for "*looping is almost always the wrong thing in sql*"
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      1. USa_horse_with_no_name
    2. COLooping implicates more-or-less "row-at-a-time" processing. And that means 2* network latency plus four context switches round trip. Yes: that is expensive. A "native" DBMS operation does all the hard work to minimise disk-I/O's (system calls) but manages to fetch more than one row per system call. Row at a time takes **at least** four system calls.
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    3. CO@wildplasser not necessary; the server could be streaming rows which you consume as they arrive - a "reader" metaphor is not uncommon.
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