dbt

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
dbt
Score 9.1 out of 10
N/A
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
Pricing
dbt
Editions & Modules
No answers on this topic
Offerings
Pricing Offerings
dbt
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Yes
Entry-level Setup FeeNo setup fee
Additional Details
More Pricing Information
Community Pulse
dbt
Considered Both Products
dbt
Chose dbt
dbt is very flexible and can fit into most data pipelines. This is a pro for most organizations that aren't fully bought into one platform (Google Cloud, etc.)
Chose dbt
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.
Chose dbt
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 …
Chose dbt
SnapLogic is great at the Extraction and Load processes of ETL. It can pull data from anywhere, even behind firewalls. So if you need to get data from various APIs, databases, files, S3, SFTP, etc it is easy to do so. However, it requires special knowledge in order to build …
Chose dbt
I haven't come across anything like DBT before.
Chose dbt
Most ETL pipeline products have a T layer, but dbt just does it better. The transformation is on steroids compared to the others. Also, just allows much more Adhoc solutions for very specific projects. Those ETL tools are probably better on the T part if you don't need too many …
Chose dbt
Airflow can accomplish the same work as dbt (data build tool), however, dbt's (data build tool) development workflow and UI can open up data transformation and modeling work to non-data engineering teams. Looker might also be able to define data models via LookML with a …
Chose dbt
dbt is great because of its transformation capabilities
Features
dbt
Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.7
8 Ratings
19% above category average
Simple transformations10.08 Ratings
Complex transformations9.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
dbt
9.1
8 Ratings
16% above category average
Data model creation9.78 Ratings
Metadata management8.78 Ratings
Business rules and workflow9.08 Ratings
Collaboration10.06 Ratings
Testing and debugging8.08 Ratings
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User Ratings
dbt
Likelihood to Recommend
10.0
(10 ratings)
Usability
9.7
(3 ratings)
User Testimonials
dbt
Likelihood to Recommend
dbt Labs
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.
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Pros
dbt Labs
  • dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
  • dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
  • dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
  • dbt can be easily integrated with snowflake.
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Cons
dbt Labs
  • Field-level lineage (currently at table level)
  • Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
  • Adding python model support (in beta now)
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Usability
dbt Labs
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.
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Alternatives Considered
dbt Labs
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.
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Return on Investment
dbt Labs
  • Simplified our BI layer for faster load times
  • Increased the quality of data reaching our end users
  • Makes complex transformations manageable
Read full review
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