dbt is used for data transformation and data engineering with multiple data transformations and engineering functions. It is also used for orchestrating data engineering pipelines. An example of this is ingesting data from Azure Blob or S3 sources and then transforming it into different layers in the data platform.
dbt Platform
dbt LabsExternal reviews
194 reviews
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Streamlined Data engineering and built-in lineages
What is our primary use case?
What is most valuable?
The best features of dbt include lineage and Jinja templating languages that make it easy for creating pipelines.
The built-in lineage feature provides a good understanding of the several layers where data is being loaded in dbt, allowing visibility from different layers into the end product.
dbt has positively impacted version controlling as it has different version control steps involved. The specific improvements seen with version control in dbt are that it has helped trace the data lineage, enabled faster trace and rollbacks, and enabled safe collaboration at every scale, which has improved data quality.
A return on investment has been seen from using dbt as the time has reduced while utilizing dbt in the form of data pipelines and ETL scripting. There is operational efficiency achieved, and data quality and governance have also been achieved with modular SQL and version controlling, which reduced duplication of data and data errors.
What needs improvement?
dbt is not as stable as preferred, as it has had a few outages in the current year itself, so improvement should be made in the outages section as it is not stable.
The copilot in dbt is not very comfortable for users, and my team has already tried using it but opted to move off from the dbt copilot to other copilots such as GitHub.
Improvement is needed in the tool itself in terms of the copilot, in terms of covering outages, in terms of testing, and in terms of quality reasons related to governance and collaboration.
For how long have I used the solution?
dbt has been used for about a year.
What do I think about the stability of the solution?
dbt is not as stable as preferred, as it has had a few outages in the current year itself, so improvement should be made in the outages section. Overall, dbt is stable.
What do I think about the scalability of the solution?
In terms of scalability, dbt has improved the scalability of the organization depending on different dimensions for team size, data, and complexity of transformations.
How are customer service and support?
The customer support from dbt was good and was identified and resolved by the customer support team when reached out to.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
Initially, multiple solutions such as Talend Studio and Informatica were utilized for different projects before switching to dbt.
How was the initial setup?
The experience with pricing, setup cost, and licensing was that it was straightforward for the pricing setup and also on the licensing part for dbt.
What was our ROI?
A return on investment has been seen from using dbt as the time has reduced while utilizing dbt in the form of data pipelines and ETL scripting. There is operational efficiency achieved, and data quality and governance have also been achieved with modular SQL and version controlling, which reduced duplication of data and data errors.
What's my experience with pricing, setup cost, and licensing?
dbt was purchased through the AWS Marketplace.
Which other solutions did I evaluate?
Before choosing dbt, other options were evaluated, but dbt was the preferred choice as it was an open-source solution that was already on the track.
What other advice do I have?
My advice to others looking into using dbt is that it is a good tool for having ETL or ELT transformations done. To begin with, a pilot project can be added with modular SQL or modeling, Git workflows, and a standardized project structure from source, staging, intermediate, to the mart layers, which will optimize performance. I would rate this solution a seven out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Efficient Data Management with Room for Documentation Improvement
What do you like best about the product?
I appreciate dbt for its secure practices in software engineering which I find crucial, particularly in ensuring integrity through data lineage, which plays a significant role in our security framework. The versatile templating system effectively enhances our data modularity, which amplifies the efficiency of our data processes. The intuitive templating also significantly improves the user experience by making our boards more operationally efficient.
What do you dislike about the product?
I wish the error messages were clearer. Sometimes, it's hard to identify the root of issues based on the current messages. Additionally, the documentation could be more beginner-friendly, as new users might find it challenging to navigate and understand.
What problems is the product solving and how is that benefiting you?
dbt resolves inconsistent data issues, making models easy to maintain. The templating boosts efficiency and data lineage ensures quality and security.
DBT review
What do you like best about the product?
Using SQL queries, it is easy platform to transform the data.
What do you dislike about the product?
For legacy system its is not useful for tranformation
What problems is the product solving and how is that benefiting you?
Data transformation
ELT made easy with just SQL
What do you like best about the product?
All I need is to write some SQL select statements and specify materialisation type. My table will be created with the type of load I want to perform.
Support tickets are resolved quickly from support team.
Support tickets are resolved quickly from support team.
What do you dislike about the product?
Sometimes the error is not described aptly. This makes parsing error and debugging difficult.
What problems is the product solving and how is that benefiting you?
DBT eliminates the need for writing complex code and tedious orchestration jobs.
I can create any model with just SQL and orchestration made easy with creating job. Tags feature with lineage made my job easy by running sequence of models.
Lineage is helpful in visualising data flow. Lint feature helps with code formatting
I can create any model with just SQL and orchestration made easy with creating job. Tags feature with lineage made my job easy by running sequence of models.
Lineage is helpful in visualising data flow. Lint feature helps with code formatting
Developer-friendly and easy to use, but doesn't have many optimization options
What is our primary use case?
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.
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.
so usefull
What do you like best about the product?
we can made maintainalble and scalable data infrastructure, this make user easy for working with data, transforming data become easy, that is why we use it in our projects also provides some standardies features
What do you dislike about the product?
we can not able to load the data from source , we can only able to use data present in dataware houses, new users may face difficulties while learning, support also not that good from community
What problems is the product solving and how is that benefiting you?
It provides standardize transformation process that help in less error, version control is also a good feature
Good if you have the software development experience and desire to manage database models as code
What do you like best about the product?
The ease, or in fact requirement, to use a repository is great if you are a developer who is used to that sort of thing and like what it offers you. Having the history of the data models tracked in this manner is great.
What do you dislike about the product?
Moves a lot of work to the data warehouse and doesn't replace an ETL tool. Nothing says dbt should be replacing an ETL tool but that's very much how I see it being used, which is unfortunate.
What problems is the product solving and how is that benefiting you?
Keeping track of changes to the database structure and the logic used in the creation of metrics is now a very simple process using dbt and a git repository. Additionally being able to easily build tests into those models is a time saver.
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