I use the solution for transformation. When we perform the ELT process, we need to transform the data according to the business requirements. We can also use the tool for testing.
dbt Platform
dbt LabsExternal reviews
173 reviews
from
and
External reviews are not included in the AWS star rating for the product.
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
Best data modeling tool
What do you like best about the product?
beautifull data lineage
easy to use and implement
dbt learning courses provided by dbt are super usefull
data sharing and orchestration is super easy
development in cloud ide is very good
custoer support is extreme fast and efficient
integration with snowflake and GitHub is easy
Using daily this tool for building data models
easy to use and implement
dbt learning courses provided by dbt are super usefull
data sharing and orchestration is super easy
development in cloud ide is very good
custoer support is extreme fast and efficient
integration with snowflake and GitHub is easy
Using daily this tool for building data models
What do you dislike about the product?
Beta features are very slow releasing. Rest all GREAT
What problems is the product solving and how is that benefiting you?
building the business models from tables and views in traditional approach is use stored procedure, routines etc. but the new way of building analytics reports and datas marts are using CTE[ common table expression] which dbt solves.
dbt also solves and give beautifull lineages, from where your source data is traversrsing to final mart layer.
table level lineage is provided by dbt and is super usefull
reporting on a single layer is solved by dbt, meaning developer need not to login to data warehouse and dot the development.
dbt separates out the data warehouse from modelling layer
dbt also solves and give beautifull lineages, from where your source data is traversrsing to final mart layer.
table level lineage is provided by dbt and is super usefull
reporting on a single layer is solved by dbt, meaning developer need not to login to data warehouse and dot the development.
dbt separates out the data warehouse from modelling layer
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.
Great experience with dbt
What do you like best about the product?
dbt is the best Transformation tool out there in the industry and I love dbt for its testing capabilities and modeling and semantic layer. Ease of use and how easily you could maintain
It is easy to integrate with other tools like integration.
It is easy to integrate with other tools like integration.
What do you dislike about the product?
dbt should add more AI apacilities faster
What problems is the product solving and how is that benefiting you?
dbt is solving all the data integration, integrity and data quality problems for our company while serving as a great transfomration tool
Developer-friendly and easy to use, but doesn't have many optimization options
What is our primary use case?
What is most valuable?
The product is developer-friendly. A person who understands SQL can develop the transformation. We do not have to learn a lot of things like we do for new tools. The tool has good testing and data quality features. Implementing Slowly Changing Dimensions through dbt has been easy. It is very easy for a beginner to use the product.
The tool provides multiple technical advantages if we use Snowflake. It is a good transformation tool because it is SQL-oriented. It has data lineage, data quality, and workflow scheduler.
What needs improvement?
The solution must add more Python-based implementations. Transformation tools require Python-based implementations. It would give developers more freedom to use SQL or Python. We can use Python, but it is not that user-friendly. The product doesn't have a lot of optimization options.
For how long have I used the solution?
I have been using the solution for almost three years.
What do I think about the stability of the solution?
There are no problems with the product’s stability.
What do I think about the scalability of the solution?
We have at least 25 to 50 users in our organization.
How was the initial setup?
The solution is deployed on the cloud. It can be deployed on AWS, Azure, or GCP. The initial setup is easy.
What's my experience with pricing, setup cost, and licensing?
The solution’s pricing is affordable.
What other advice do I have?
We also use stored procedures and Talend. They are not replaced by dbt completely. We use dbt only for the transformation process. My recommendations would depend on an organization’s requirements and problems. I will recommend the tool to others. The product is developer-friendly. However, it is still dependent on the data warehouse for big data and optimization.
It's just a SQL transformation tool. It doesn't have a lot of optimization options like Spark. It's a good tool for Snowflake. If it were only for Snowflake, I would have rated it an eight out of ten. However, there are other data platforms.
Overall, I rate the tool a six and a half out of ten.
Deal with data transformations with flexible learning curve and handle big data workloads
What is our primary use case?
We use the solution to deal with data transformations inside different organizations.
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.
showing 11 - 20