Improving Data Integration with ODBC
Recently, I’ve touched upon the topic of data integration with ODBC. Today, I’d like to add some more words. Successful data integration with ODBC sources depends on many things of which not the least is the performance of ODBC applications. There are several factors that affect ODBC performance. Improvements of those factors help make ODBC applications faster which, in turns, help improve and avoid issues in data integration. Here the factors are:
- Network communication
Reducing network communication may increases ODBC performance multiple times. Arrays of parameters used instead of Insert statements, for example, reduce the time required to complete the operation.
- Choosing the way the transactions are handled
To improve ODBC performance it’s essential to choose the right way transactions are handled. Thus, for example, using manual commits instead of auto-commits gives better control over the work committed.
- Connection pooling
When an ODBC application has several users connection pooling is a good way to increase connection efficiency.
- SQL queries
Efficiency of SQL queries is an important factor affecting the speed of ODBC performance. If something is wrong with it, issues may occur with data filtering causing the driver to get unnecessary data (sometimes the amount of this data is very big) which slows down application performance. Using well-formed and rightly executed queries improves the performance greatly.
ODBC provides good opportunities in data integration, giving an access to multiple data sources through one application. So keeping the application’s performance high will benefit the process of data integration.