Building the Right Environment to Support AI, Machine Learning and Deep Learning
Direct usage of ODBC is very complex. Anybody who tries to work with ODBC can say it. Also, ODBC is a function-level interface. It is a good universal interface, but all structured C++ applications look very horrible when plain ODBC calls are used.
I want to offer a little library, which:
- Wraps access to ODBC into a set of classes
- Wraps processing of ODBC and usage errors into an exception mechanism
- Doesn't use any external libraries, including MFC and ATL
- Doesn't require any special conditions to use it
- Automates column binding operations
- Can automate (for MSSQL server) binding of parameters
- Can provide transparent work with LOB columns/parameters without limitation of their size
- Has a Help file, even if this Help file is simple
- Is freeware, open-source library
- Supports powerful local-side cursors with indexing and modifying of cursor(insert, update, delete) are supported
DownloadsDownload source - ~140 Kb
Contains sources of library and Help files.
Download demo project - ~70 Kb
Contains project with a demonstration of the library usage.