Complex processing in Stored procedures Vs .net application

Question

We are building a new application in .net 3.5 with SQL server database. The database is fairly large having around 60 tables with loads on data. The .net application have functionality to bring data into this database from data entry and from third party systems.

After all the data is available in database the system have to do lots of calculation. The calculation logic is pretty complex. All the data required for calculations is in database and the output also needs to be stored in database. The data gathering will happen every week and the calculation needs to be done every week to generate required reports.

Due to above scenario I was thinking do all these calculations using Stored Procedure. The problem is we need data independence also and stored procedure will not be able to provide us that. But if I do all this in .net by query database all the time, I don't think it will be able to finish the work quickly.

For example, I need to query one table which will return me 2000 rows then for each row I need to query another table which will return me 300 results than for each row of this I need to query multiple tables (around 10) to get required data, do the calculation and store the output in another table.

Now my question should I go ahead with stored-procedure solution and forget about database independence since performance is important. I also think development time will be much less if we use stored procedure solution. If any of client want this solution on say oracle database (because they don't want to maintain another database) then we port the stored procedures to oracle database and maintain two versions for any future changes/enhancements. Similarly other clients may ask for other databases.

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The 2000 rows which I mentioned above is of product skus. The 300 rows I mentioned is of different attributes which we want to calculate, e.g. handling cost, transport cost, etc. The 10 tables I mentioned have information about currency conversion, unit conversion, network, area, company, sell price, number sold per day, etc. The resulting table stores all the information as a star schema for analysis and reporting purpose. The goal is to get any minute information about the product so that one know what attribute of a product selling is costing us money and where we can do the improvement.

Answer 1

I wouldn't consider doing the data manipulation anywhere other than in the database.

most people try to work with database data using looping algorithms. if you need real speed, think of your data as a SET of rows and you can update thousands of rows within a single update. I have rewritten so many cursor loops written by novice programmers into single update statements where the execution time was massively improved.

you say:

I need to query one table which will return me 2000 rows then for each row I need to query another table which will return me 300 results than for each row of this I need to query multiple tables (around 10) to get required data

from your question it looks like you are not using joins, and you are already thinking in loops. even if you do intend to loop, it is much better to write a query to join in all data necessary then loop over it. remember update and insert statements can have massively complex queries driving them. include in CASE statements, derived tables, conditional joins (LEFT OUTER JOIN) and you can just about solve any problem in a single update/insert.