dbt Platform
dbt LabsExternal reviews
194 reviews
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Really helpful for cleaning up data
What do you like best about the product?
The product is really good, but the support documentation and community surrounding the product are really helpful in implementing the product.
What do you dislike about the product?
It takes a lot of training to get competent with the product - not unexpected.
What problems is the product solving and how is that benefiting you?
Orchestrating our data into usable models
dbt review
What do you like best about the product?
Highly functional SQL transformational tool. Simple to start, but with adequate levels of complexity available to add if necessary. Good documentation.
What do you dislike about the product?
Nothing comes to mind as the product provides a great solution
What problems is the product solving and how is that benefiting you?
Internal data transformation in a cloud warehouse. Very few other products accomplish this as well.
Great tool - fast development experience
What do you like best about the product?
Time saving of having fully integrated tool - faster development experience than managing my own IDE, query tool and command line/git
What do you dislike about the product?
git branches that are deleted still stick around for some reason, dark mode glitches and becomes light mode on some tabs, SQL preview window glitches and freezes
What problems is the product solving and how is that benefiting you?
Collaborating on data pipeline design and creation of data assets
dbt is a great tool, I wouldn't want to be without it
What do you like best about the product?
Most helpful is how dbt sorts out dependencies for you. Using references in your models, you can tell immediately if a column name change has caused a problem downstream. The DAG graph is fantastic, particularly in the dbtCloud IDE as it updates immediately. Adding basic tests is easy, leading to increased levels of confidence. I know I can run and rerun things without causing problems. If tests pass we're good to go. Freshness tests help make sure that nothing is run if upstream data is not present. This has helped us considerably recently. And exposures, linking to external reports that use the data, is really useful.
What do you dislike about the product?
Creating a job in the dbtCloud interface and having it default to an hourly schedule. We've only had one minor mishap, but that could be costly with BigQuery. Unless I've missed a setting, that should be off by default.
I don't use the Web IDE. Personal preference, I don't want to switch editors. But the lineage graph is awesome, and seeing the compiled alongside the editor is a great feature.
I don't use the Web IDE. Personal preference, I don't want to switch editors. But the lineage graph is awesome, and seeing the compiled alongside the editor is a great feature.
What problems is the product solving and how is that benefiting you?
Getting data under test so that we know the data makes sense, not just that it has been loaded. The freshness tests have increased confidence that reports are ready to send from our BI tool. We have a history of many similar queries doing the same work. We're using dbt to find and eliminate that duplicated work.
UI based Version Control and ETL Orchestration
What do you like best about the product?
DBT Cloud lets users set up transformations and orchestrate code runs from a UI-based IDE in the cloud for users who aren't as familiar with using the command line. By leaving engineers to do the coding rather than spending time digging through documentation, our team could reach functionality faster and with less fuss than expected. The ability to test in a safe environment by default before you push your changes to live makes version control easy for users not familiar with git principles.
What do you dislike about the product?
The cloud-based IDE has a long-ish startup time (30 seconds or longer) and locks you out of editing while it syncs after you save a file. This leads to a little bit of frustration when making minor edits across multiple files. Some other minor frustrations related to the Cloud IDE come to mind, like how column names aren't sensed while you're typing, leading the user to write out column names that could be easily polled during the lineage population. In addition, the testing documentation was a little confusing, leading to me trying different things to get it to work. In the end, I learned that you have to prefix the name of a test model with "test_" to get the orchestrator to see the model as a test. However, after a couple of speed bumps, most issues I have turn out to be minor and do not impact the product's overall usefulness.
What problems is the product solving and how is that benefiting you?
DBT Cloud has allowed us to migrate from one ETL partner and re-create our transformation files with version control and replicability in mind first and foremost. Additionally, for users who aren't familiar with command line interfaces, we can spin up new users and share work easily while everyone can push to the same deploy environment.
Modern day - Data Transformation Tool !
What do you like best about the product?
It's very well thought out and designed.
What do you dislike about the product?
Changing versions and keeping up to date with the changes
What problems is the product solving and how is that benefiting you?
- Platform dependencies resolved
- Visualization of data flow
- Easy to use, improvise and adapt
- Community Support
- Visualization of data flow
- Easy to use, improvise and adapt
- Community Support
game changer technology
What do you like best about the product?
Data Catalog Feature. You can just build out your data warehouse while catalog feature takes care of documentation for you.
What do you dislike about the product?
None. Maybe it would be a bit challenging for people who are not familiar with version control.
What problems is the product solving and how is that benefiting you?
Building out Data Warehouse and Data Marts while documenting the transformation with data catalog feature. Also save a lot on data engineering time
Love it, so far. Still getting up to speed.
What do you like best about the product?
Could based; transparency of how everything is built and executed; the support from dbt and the user community; integrated documentation, testing, and git repository; dbt leverages team SQL knowledge.
What do you dislike about the product?
How to find and use packages and macros is not intuitive. If you're new to dbt, it's hard to know what's available, or how to approach a specific use case.
What problems is the product solving and how is that benefiting you?
Loading data vault on snowflake. We are replacing another tool that was too cumbersome and inefficient.
dbt is easy dynamic sql on steroids
What do you like best about the product?
easy to learn, very dynamic and powerful. dbt allows teams to work together using skills they already know (sql) along with a powerful templating language. this allows you do develop dynamic sql in a very easy, maintainable fashion. Using text files, it also allows you to easily see what's changed and who made those changes via github integration. It also eliminates the tedious ddl creation, and allows you to switch between using views and tables with a single configuration argument. It has powerful testing capabilities built in.
What do you dislike about the product?
compiling sometimes when not needed - it can slow down your development if you're saving a lot of files at once. Usually performance is not a problem but in some cases (not the typical workflow) it can be slow.
What problems is the product solving and how is that benefiting you?
solving data transformations. dbt lets you create dynamic sql very easily. you can onboard new teammates easily as everyone knows sql. transformations are stored in plain text in github so you can easily identify what's changed. easy to use - you only write 'select' statements - dbt handles all the ddl for you dynamically, keeping target environments separate. Integrated documentation and testing. packages (libraries) are available with great utilities.
Recommendations to others considering the product:
dbt is great for transformation - you still need another tool like FiveTran or Stitch to get the data into your warehouse. It's very powerful, and the dbt tools and support are great. Onboarding is quick as there are many developers who know sql. Being familiar with python is an additional bonus to becoming productive rapidly, but not required. One thing I really like is that dbt is open-source, so you can keep your business logic transformations even if you decide not to use dbt cloud. In most other etl tools, if they hike the rates you are stuck using their product or re-writing everything from scratch. dbt core offers a good alternative under those circumstances. However, the company provides good value for its services so I'm happy to stay with them.
With a prior GUI-based tool it was impossible to easily see what had changed, and merge with other developers. This is built for teamwork and accountability.
There are also out-of-the-box tools and libraries that can help you test and maintain data quality with no coding required.
The online dbt documentation is very good. In addition to regular support, they have slack channels and are very responsive.
The online training and personalized rapid onboarding training was excellent too.
Using dbt we were able to set up a Snowflake data warehouse and bring in 21 different sources, servicing hundreds of reports, in 8 months with a team of 2-3 data engineers and 3 BI engineers.
With a prior GUI-based tool it was impossible to easily see what had changed, and merge with other developers. This is built for teamwork and accountability.
There are also out-of-the-box tools and libraries that can help you test and maintain data quality with no coding required.
The online dbt documentation is very good. In addition to regular support, they have slack channels and are very responsive.
The online training and personalized rapid onboarding training was excellent too.
Using dbt we were able to set up a Snowflake data warehouse and bring in 21 different sources, servicing hundreds of reports, in 8 months with a team of 2-3 data engineers and 3 BI engineers.
Very powerful tool
What do you like best about the product?
DBT is critical to my organization and so far the tool has been very simple to use. My favorite feature is the interactive flowchart! absolutely game changing
What do you dislike about the product?
I think editing in DBT could get a little confusing with the different steps that are needed to update the code.
What problems is the product solving and how is that benefiting you?
We use DBT to clean and transform our data before it is synced into our BI tool
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