I get around this, and other issues such as collation issues between SQL Server and Excel, by always passing dates to Excel as text in a format of dd-MMM-yyyy e.g. '01-Jan-2014'.
It's not pretty but it has worked so far...
“That which can be asserted without evidence, can be dismissed without evidence.”
Error starting at line : 17 in command -
Error at Command Line : 17 Column : 1
Error report -
SQL Error: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'END $$' at line 1
I am using Oracle SQL Developer and the INSERT statement works ok when executed on its own. I can do these things blindfolded with my arms tied on MSSQL. Any help appreciated.
Just store the filenames without the path to the file server in the database table. Store the path to the file server separately say in another database table and concatenate it with the filename by code whenever user wants to access a file.
Instead of using a plain database back-end, create a server which communicates with the clients and the database. So any client will contact the server which in turn talks to the database and file system, and serves the data/documents back to the clients.
There are differences in query keywords and functionality; also differences in datatypes (MySQL does not have a Guid datatype). Also MySQL has some strange calculation bugs when dealing with DateTime values. Escaping reserved keywords uses different characters. Etc...
You cannot simply replace MS SQL Server and MySQL, you'll need to adjust your application to the database!
For some reason I won't explain here it happens that companies or countries block some websites. Some companies block everything except professional website like this one (codeproject) or Microsoft or universities, ... But blogs are blocked.
That the reason I don't like when people answer to go to check on Google or other search website.
A traditional transactional database is made for storing data. These databases are generally highly normalized to keep the referential integrity, but might be to slow for analytical queries.
A data warehouse is optimized for analysis of the data. The data is therefore often stored in a denormalized and/or aggregated form. To make sure the referential integrity is kept intact they usually pull their data from a transactional database.