Excellent Utility Environment Across Multiple Data Sources
Use Cases and Deployment Scope
I work as a data scientist, marshalling and summarizing data for model-making and analytics to be run against it. I use Toad as a development and query environment against our corporate data warehouse, which encompasses multiple data sources. The target is a Netezza data appliance and the majority of work we do utilizes standard, uncomplicated SQL against
Pros
- Connects to multiple data sources
- Allows code folding to encourage focus on subsections of code
- Is standard across multiple database engines
- Is stable and well documented across its history
Cons
- Leaks memory in Windows 10 (at least as currently configured)
- Occasionally hangs and requires a restart
- Some operations are either multi-step or unintuitive
- Does not support extensions to change functionality
Return on Investment
- It is the least common denominator - not particularly optimized for our environment or workflows.
- Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
- Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
- It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.
Alternatives Considered
SQL Server Management Studio (SSMS) and Microsoft Visual Studio Code
Other Software Used
SQL Server Management Studio (SSMS), Microsoft Visual Studio Code, Notepad++



