dbt vs. erwin Data Modeler

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

If you have a database environment that gets frequent schema object change requests. erwin Data Modeler is a great tool for version control and release control. Also, it's very useful to communicate between database and application teams.

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

• Creation of logical data models
• Reverse engineering
• Excellent communication tool in conversations with Developers and BAs
• As a company, Erwin provides lots of tutorials and how-tos.

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

• erwin Data Modeler allows only 25 entities in a trial version. It really limits you when you want to try out the product before actually deciding to pay for licensing cost. It would be rather helpful if they limit the trial period by days instead.
• The UI is pretty good but sometimes the large diagrams are hard to manage. A little improvement in that area would be helpful.

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

The product is well designed and intuitive to use. The number of buttons and options can look a bit overwhelming initially but they come very handy when you get used to product.

Incentivized

CA customer support and our account manager have been able to support us with any issues that we have had, from managing our serial keys to issues we logged tickets to resolve. There are aspects of key management that have made it difficult over the years but support usually has worked with us.

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

I have used few other data modeling tools like Toad Data Modeler and SQL Developer Data Modeler. erwin Data Modeler is easy to use and has additional features that make overall data modeling productive and easy to manage.

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

• Reduced rework from when models were maintained individually.
• Reduced the amount of time to generate and compare models during development.
• Massively reduced the amount of time to reverse engineer 3rd party data models for analysis.

Incentivized