We use the solution to deal with data transformations inside different organizations.
dbt Platform
dbt LabsExternal reviews
185 reviews
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We finally brought order to complex metric definitions
What do you like best about the product?
It is very nice that dbt gives us the capability to write out our transformation logic as application code. The process of integrating it with Git implies that our whole team may contribute to data models and track changes without hassles, and revert changes as well. Even the separation of the development and production environment out of the box is a tremendous advantage, so we can ensure that we are testing new things without necessarily influencing live reports. Lastly, the automated documentation generation process has made the data models so simple to comprehend, even to the business users, without ever having the touch a SQL.
What do you dislike about the product?
The initial set up of dbt can be a little fiddly at times and with a mix of operating systems and local database connections. It also lacks its own scheduler, so still we will require an external orchestration tool to carry out our data pipelines. The more advanced Jinja templating and macros proved to be more cumbersome to our team to learn than the simpler SQL.
What problems is the product solving and how is that benefiting you?
Our greatest weakness prior to dbt was inconsistent reporting amongst departments, this contributed to lack of numbers and big debates on the correct numbers between departments. Marketing could report a figure of new customer acquisition and sales could report an entirely different figure and that could slow down decision making. I we have one version controlled definition of all of our critical business metrics since dbt is in place. Such change came to mean that our leadership team trusts the figures implicitly and no longer spends so much time on reconciliation of numbers, but can actually analyze them.
DBT review
What do you like best about the product?
DBT is user friendly and helps keep our data reliable, updated and secure
What do you dislike about the product?
Upgrading from core is really expensive without there being any significant differences besides number of users
What problems is the product solving and how is that benefiting you?
DBT helps us build our models and keep them refreshed in our warehouse
Elevating Our Data Stack
What do you like best about the product?
dbt's ability to streamline data workflows is excellent
What do you dislike about the product?
While dbt is great, for extremely large datasets or highly complex transformations, native SQL compilation might still require deep optimization knowledge or workarounds to achieve peak performance
What problems is the product solving and how is that benefiting you?
Streamlining our data workflows and ELT process
DBT at my point of view
What do you like best about the product?
Data transformation logic can be expressed in SQL
Data can be transformed in batch
Ease to use, it has lot of good features similar in Django web application
Data can be transformed in batch
Ease to use, it has lot of good features similar in Django web application
What do you dislike about the product?
Joining multiple database types is not possible. Ie., combining two databases like oracle and mysql.
Persistent cluster is required for running the sql statements.
Like Presto/Hive it can’t be connected to BI Directly
Persistent cluster is required for running the sql statements.
Like Presto/Hive it can’t be connected to BI Directly
What problems is the product solving and how is that benefiting you?
Enables engineers to transform data in their data lakehouse using select statements in SQL.
Converts SQL select statements into Tables or Views
Supports DW process such as incremental, SCD etc.,
Graphical representation of pipelines
Converts SQL select statements into Tables or Views
Supports DW process such as incremental, SCD etc.,
Graphical representation of pipelines
We majorly use DBT cloud for ETL in the organization
What do you like best about the product?
It's simple, SQL based approach and easy to version control.
What do you dislike about the product?
Challenging to manage large scale and complex dependencies
What problems is the product solving and how is that benefiting you?
Since it's SQL based, its easy to manage ETL pipeline.
DBT(Data Build Tool) to build Excellent data models for Quickly and collaboratively
What do you like best about the product?
The most and best things i like in dbt are it not only helps in creating transformations but can also helps in managing and performing transformations in a view and integrates easily with Big-query
i can use and configure the transformation as per the object like table,view or incrementalalong with features like auto-generated lineage graphs and can perform native testing with few lines of codes in a YAML file and can able to re use them.
i can use and configure the transformation as per the object like table,view or incrementalalong with features like auto-generated lineage graphs and can perform native testing with few lines of codes in a YAML file and can able to re use them.
What do you dislike about the product?
There is not much about to dislike in dbt the reusable code can be little bit confusing and jumping from one branch to another can be frustrating
What problems is the product solving and how is that benefiting you?
DBT helped me and my team in testing data pipelines in local in house development
and Performing CI/CD pipeline tests along with data migration to targets like Bigquery.
and Performing CI/CD pipeline tests along with data migration to targets like Bigquery.
A game changer for dashboarding
What do you like best about the product?
You would feel really strange at first but after you start the integration will notice how easy to use it is. Great Documentation and community.
What do you dislike about the product?
The initial deployment is not ideal, and it would be beneficial to have a interface for dbt Core to support analysts who do not use Git on a daily basis but still take advantage of its benefits.
What problems is the product solving and how is that benefiting you?
Create an UI for some tools like dbt core that would help non tech people give a try to the product
It was good
What do you like best about the product?
To build reliable data models quickly and collaboratively
What do you dislike about the product?
It should be more accesible with more features
What problems is the product solving and how is that benefiting you?
Problems related with Data visualizations and optimizations
Overwhelming when it comes to optimize and centralize your big data.
What do you like best about the product?
1. The documentation it generates when all the models are designed. It clearly defines which intermediate and final layers are connected to each other.
2. The incremental model runs greatly helped me in optimizing large data models as I was dealing with billions of rows of data.
2. The incremental model runs greatly helped me in optimizing large data models as I was dealing with billions of rows of data.
What do you dislike about the product?
I did not come across any difficulty in learning DBT as it was pretty basic and I also applied SQL fluff to streamline my coding. As a user, I did not find much difficulty in operating through dbt.
What problems is the product solving and how is that benefiting you?
Previously, I was using GBQ for creating thousands of lines of stored procedures and so many tables were interconnected inside of it. It was pretty difficult to determine which tables are made up of what.
When I started using DBT, I was able to quickly determine and find the staging and intermediate layers for the purpose of creating a final layer and the documentation it creates was awesome.
I am talking about dbt docs generate and dbt docs serve.
When I started using DBT, I was able to quickly determine and find the staging and intermediate layers for the purpose of creating a final layer and the documentation it creates was awesome.
I am talking about dbt docs generate and dbt docs serve.
Deal with data transformations with flexible learning curve and handle big data workloads
What is our primary use case?
How has it helped my organization?
You need some knowledge. Dbt has a more flexible learning curve than other tools. You need some experience to handle big data workloads but with less experience, you can get started.
What is most valuable?
They help us orchestrate different transformations. With Dbt, you can automate the orchestration of transformations without thinking too much.
What needs improvement?
SQL statements that beyond DML, are not possible. Currently, they are not possible in Dbt. Having more features in SQL statements will support us.
Another issue is the terms of data ingestion because Dbt requires sources to be defined, and you need to handle data ingestion with other tools. So having a data injection tool integrated within dbt will be awesome.
For how long have I used the solution?
I have been using dbt for three years.
What do I think about the scalability of the solution?
It's very scalable because it's open source. You can spin up different EC2 or different compute instances to run VVT. We have 14 professionals using this solution. I rate it a nine out of ten.
How was the initial setup?
I store procedures calling within dbt statements. You can only use a selected statement in debt. If you want to use more advanced or more complicated SQL features, they are not supported right now by Dbt, so that can be a challenge.
What's my experience with pricing, setup cost, and licensing?
It is cheap because dbt is open source. If you compare the pay-per-service of Dbt with the open source option you can manage. We are managing the solution, when we were acquiring service from them. It was also cheap compared with the engineering cost that implies managing the the infrastructure.
What other advice do I have?
I have had the opportunity to teach one of the tools to level entry engineers because it's easy to learn and easy to maintain. It's pretty useful.
It depends on the architecture and the amount of company's data or the people that I'm going to advise. If you're starting a data engineering team and you don't have a lot of big data workflows, I would recommend Dbt. I recommend our tools for more advanced workflows but for starting, I recommend 100% Dbt.
Overall, I rate the solution a nine out of ten.
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