The App is continuously upgrading. It's becoming more user-friendly and bettering the user experience. SQL writing becoming very quick. Review collected by and hosted on G2.com.

The customer support panel is always down. I have waited long many times for the help but it didn't arrive. Review collected by and hosted on G2.com.

The best thing about dbt is how easy it is for you to load and transform the data using some built-in features. They listen to the community's problems and are always updating by adding packages and new features to make your life easier. Review collected by and hosted on G2.com.

If there was any downside, dbt had already solved it by introducing new features and adapting to the problems that the community has faced. Review collected by and hosted on G2.com.

- Easy to use and deploy for someone with SQL background

- Great community of support

- Easy to launch and maintain

- Can support data quality testing Review collected by and hosted on G2.com.

- Complex transaofrmations which require python gets harder Review collected by and hosted on G2.com.

dbt is excellent due to its wide use of macros and the ability to transform data using SQL, an analyst-friendly language. Given this we can train analysts to read dbt and understand the logic behind our data transformations, limiting the amount of work we need to do explaining data decisions or documenting logic. Review collected by and hosted on G2.com.

I wish that dbt was more integrated with other data tools. It seems that a lot of data tools (fivetran, monte carlo, hightouch) are designed with dbt in mind but dbt never seems designed for these tools. It would be nice to have more accessibility within dbt, allowing us to create alerting and etl processes easier. Review collected by and hosted on G2.com.

DBT is an easy to use tool for anyone who knows SQL. Their IDE is wonderful and you can easily spin it up in no time. As a Data Scientist, doing modeling in DBT saves me hours of work and helps me provide an opportunity to others to focus on a more self-serve analytics. Review collected by and hosted on G2.com.

DBT is a great tool but there are a few things missing from it. Direct connection to PostgreSQL. Mixing of different sources and more convenient ways of building tests and macros. Review collected by and hosted on G2.com.

One of the best things about dbt is that because it's an Sql-based platform, anyone ranging from a Data Analyst to a Data Engineer can easily implement and deploy Data Pipelines. It provides integrations with any different data sources like postgres, Snowflake, Bigquery etc along with features like CI/CD and version control. Review collected by and hosted on G2.com.

Currently dbt only focuses on the transformation aspect of a data pipeline. It can also focus on Data quality. Review collected by and hosted on G2.com.

Automatically created ERD diagrams and much more metadata about models built. Review collected by and hosted on G2.com.

Updating versions can be time consuming and cumbersome. Review collected by and hosted on G2.com.

DBT is an all in one tool. You dont have to leave the plaform to get the things done in the right way. The readibility and code structure is very nice. Review collected by and hosted on G2.com.

The documentation is not very extensive. Review collected by and hosted on G2.com.

It brings best software development best practices to a world that didn't have them natively several years ago.

It helps speed up the delivery of data transformation models and consumable data.

It provides more than a data transformation framework, tests and documentation are two very welcome features to it. Review collected by and hosted on G2.com.

Some people may have a hard time getting to know the framework; for this, the courses on the dbt website are a great introduction.

For people coming from a traditional drag & drop (no code) tool, the change of mindset is even more challenging. There are no training materials for addressing the "this is how you did it with a traditional tool" and "this is how you do it with dbt", so these have to be created internally by each data team. Review collected by and hosted on G2.com.

Dbt has revolutionized the way we handle data transformations in our organization. It's incredibly easy to apply and use, even for non-technical team members. With its intuitive command-line interface and well-documented features, we were up and running in no time.

One of the standout features of dbt is its ability to implement software best practices to our SQL codebase. It promotes modularization, version control, and testing, allowing us to treat our data transformations as a software project. This has significantly improved our code quality, collaboration, and overall data reliability. Top it with great, constantly growing, supportive community and a number of integrations with data observability and cataloging tools, third-party modules and libraries.

Dbt is simply a great product. Its support for various data warehouses gives us the flexibility to work with our preferred platform, and the performance optimizations, such as incremental processing, have saved us valuable time and resources.

I consider dbt a must-have for every data tech stack. It has streamlined our data pipeline development and maintenance, ensuring consistency and accuracy throughout our analytics models. Whether you're a data analyst, engineer, or scientist, dbt empowers you to transform raw data into valuable insights with ease.

In fact, i was headhunted and hired for my current role, primarily because of my dbt knowledge.

Dbt has exceeded my expectations on all fronts since day one and keeps doing it as it develops, it has become a number one tool in my professional armamentarium. Its simplicity, adherence to software best practices, and overall functionality make it a standout choice for anyone working with data. Review collected by and hosted on G2.com.

Nothing, that is truly a great tool, created by a great team. Review collected by and hosted on G2.com.