dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
$0
per month per seat
Git
Score 10.0 out of 10
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Pricing
dbt
Git
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dbt
Git
Free Trial
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No
Free/Freemium Version
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Premium Consulting/Integration Services
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Entry-level Setup Fee
No setup fee
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dbt
Git
Features
dbt
Git
Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.7
8 Ratings
19% above category average
Git
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Ratings
Simple transformations
10.08 Ratings
00 Ratings
Complex transformations
9.48 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.
GIT is good to be used for faster and high availability operations during code release cycle. Git provides a complete replica of the repository on the developer's local system which is why every developer will have complete repository available for quick access on his system and they can merge the specific branches that they have worked on back to the centralized repository. The limitations with GIT are seen when checking in large files.
Git has met all standards for a source control tool and even exceeded those standards. Git is so integrated with our work that I can't imagine a day without it.
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.
I am not sure what the official Git support channels are like as I have never needed to use any official support. Because Git is so popular among all developers now, it is pretty easy to find the answer to almost any Git question with a quick Google search. I've never had trouble finding what I'm looking for.
I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.
I've used both Apache Subversion & Git over the years and have maintained my allegiance to Git. Git is not objectively better than Subversion. It's different. The key difference is that it is decentralized. With Subversion, you have a problem here: The SVN Repository may be in a location you can't reach (behind a VPN, intranet - etc), you cannot commit. If you want to make a copy of your code, you have to literally copy/paste it. With Git, you do not have this problem. Your local copy is a repository, and you can commit to it and get all benefits of source control. When you regain connectivity to the main repository, you can commit against it. Another thing for consideration is that Git tracks content rather than files. Branches are lightweight and merging is easy, and I mean really easy. It's distributed, basically every repository is a branch. It's much easier to develop concurrently and collaboratively than with Subversion, in my opinion. It also makes offline development possible. It doesn't impose any workflow, as seen on the above linked website, there are many workflows possible with Git. A Subversion-style workflow is easily mimicked.
Git has saved our organization countless hours having to manually trace code to a breaking change or manage conflicting changes. It has no equal when it comes to scalability or manageability.
Git has allowed our engineering team to build code reviews into its workflow by preventing a developer from approving or merging in their own code; instead, all proposed changes are reviewed by another engineer to assess the impact of the code and whether or not it should be merged in first. This greatly reduces the likelihood of breaking changes getting into production.
Git has at times created some confusion among developers about what to do if they accidentally commit a change they decide later they want to roll back. There are multiple ways to address this problem and the best available option may not be obvious in all cases.