dbt vs. Toad Data Point

dbt (Data Build Tool) is best suited for doing the data transformation. dbt is just a transformation tool and it is not suitable for building a data pipeline which requires extraction of data and loading. dbt is well suited for SQL based transformation logic and it is less appropriate when transformation logic requires python.

Incentivized

Toad Data Point is the clear tool of choice if the end-user is interested in reports that are relatively simple to build using SQL code and export to Excel. It is less useful if the analyst also needs to run statistical models on the data and visualize the data for those functions I usually use RStudio or Jupyter Notebook which incorporates those features much more seamlessly.

Incentivized

• user experience makes it easy to work with SQL and version control
• customer success team and the dbt (data build tool) community help establish best practices
• thorough and clear documentation

• Ease of use. It is a very easy product to use without any particular training.
• Multiple data source connection. It easily connects to multiple data sources which allows you to use different data sources to run reports.
• Seamless application. Once you set everything up-- whether it is an FTP or export of data-- you can set it and forget it!

Incentivized

• Slow load times of the dbt cloud environment (they're working on it via a new UI though)
• More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros

Incentivized

• The program can error out when reconnecting to a database from a timeout but that is easily fixed by restarting the program.
• If you aren't familiar with database tools the UI can be overwhelming to some.

Incentivized

dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.

Incentivized

I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap

Incentivized

Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.

Incentivized

TOAD excels at connecting to divergent data sources, but appears geared more to DBAs than to regular query users. Microsoft's offerings excel against Microsoft SQL Server, but sometimes struggle with other data sources. However, SSMS and vs code excel at many developer productivity/workflow enhancements. vs code, in particular, has a lively extension system that allows it to be tailored for development/querying/model building/etc. That flexibility comes at a cost - the learning curve is steep for new users. The tradeoff between complexity and power may not be good for some environments/users/situations.

Incentivized

• In 3 months we re-wrote the data warehouse (15-20 sources) in dbt with 3 developers.
• We are using it continually for the past year with no issues.
• Sorry, I don't have ROI numbers but the impact was huge.

Incentivized

• 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.

Incentivized