Sold by: dbt LabsÂ
Deployed on AWS
dbt Platform is a hosted service that helps data analysts and engineers product-ionize dbt deployments. It comes equipped with turnkey support for scheduling jobs, CI/CD, serving documentation, monitoring & alerting, and an Integrated Developer Environment (IDE).
4.7
Overview
dbt is an open source data transformation tool that allows anyone comfortable with SQL to author their own data pipelines. dbt Platform provides a stable, professional grade environment for building and orchestrating dbt projects. It's the fastest and most reliable way to deploy dbt.
Find out if dbt Platform works with your data base or data warehouse here: https://docs.getdbt.com/docs/available-adaptersÂ
Sign up for a free, 14-day trial here: https://www.getdbt.com/signup/Â
Highlights
- Save time with an IDE built for dbt, including a SQL Runner capable of running Jinja; and guided process to enforce version control best practices, even for users new to git
- Set up custom schedules to run production jobs including incremental testing upon change or before deployment.
- dbt Platform provides professional grade support and security for the enterprise (SOC2, Type II compliance, SSO, role-based access)
Details
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Delivery method
Deployed on AWS
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Dimension | Description | Cost/12 months |
|---|---|---|
dbt Platform | dbt Platform Plan: 10 Develop Licenses | $48,000.00 |
Dimension | Cost/unit |
|---|---|
Additional overages as defined in contract | $0.01 |
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Support
Vendor support
Complete documentation is available at https://docs.getdbt.com/docs/dbt-cloud/cloud-overview/Â . support@getdbt.comÂ
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Pipeline Transformation
Open source SQL-based data transformation tool for building and orchestrating data pipelines
Integrated Development Environment
SQL Runner with Jinja support and version control workflow guidance
Job Scheduling
Custom scheduling capabilities for production jobs with incremental testing and deployment options
Enterprise Security
SOC2 Type II compliance with single sign-on and role-based access control mechanisms
Deployment Orchestration
Professional-grade environment for stable and reliable dbt project deployment and management
AI-Powered Development Environment
Integrated code IDE with native AI capabilities for data engineering and analytics development
Pipeline Orchestration
State-aware scheduling system for dbt and Python data pipelines with advanced monitoring capabilities
Data Lineage Tracking
Column-level lineage context and impact analysis for comprehensive data transformation workflows
Multi-Platform Integration
Supports seamless integration with data ingestion and visualization tools like Fivetran, Tableau, and PowerBI
Performance Optimization
AI-driven agents for continuous warehouse cost monitoring and operational efficiency
Environment Management
Automated Snowflake infrastructure management using configuration and code deployment
Pipeline Orchestration
End-to-end data pipeline construction and tool integration for data ingestion, modeling, and testing
Continuous Integration/Deployment
Comprehensive CI/CD capabilities for data engineering workflows with automated testing and code management
Observability Framework
Unified metadata collection and management providing comprehensive operational insights across data products
Development Workflow
Integrated development environment supporting Snowflake workload development, testing, debugging, validation, and execution
Standard contract
Customer reviews
JohnnyHuang
Coding-focused data pipelines have accelerated delivery of in-house data products
Reviewed on Dec 02, 2025
Review from a verified AWS customer
What is our primary use case?
My main use case for dbt is for data transformation and data engineering.
A specific example of how I use dbt for data transformation and engineering is that we use it to connect and ingest data from our Azure blob and S3 buckets, then transform through our glorified serving layers into our data platform.
We use dbt to orchestrate our data engineering pipelines.
What is most valuable?
The best features dbt offers include built-in lineage, which is useful, and the Jinja templating language that makes it easy for creating pipelines.
The built-in lineage feature and the Jinja templating have made things easier for me because it's an easy language that most people pick up pretty quickly, and the ability to template SQL and generate SQL programmatically is useful.
dbt has positively impacted my organization by allowing us to create our data pipelines much faster, going from ingestion of data to creating a data product in weeks instead of months, and we can do it in-house with the skillset we already have.
I can share a specific outcome that resulted from using dbt: there was a data product a vendor did for us two years ago that took them six months to achieve, whereas we were able to do it in-house with dbt coupled with Snowflake in four to five weeks, which was much quicker.
What needs improvement?
dbt can be improved as I find the co-pilot in dbt is not very good, and my team has tried using it but opted to move off it and use other co-pilots such as GitHub . Additionally, the debugging capabilities in dbt are practically nonexistent, making it very hard to troubleshoot and debug if you write incorrect Jinja code.
dbt is not as stable as I would prefer, as there have been a few outages this year.
For how long have I used the solution?
I have been using dbt for about four years.
What do I think about the scalability of the solution?
dbt's scalability is fine, and I have never had any capacity problems.
How are customer service and support?
The customer support is average.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I previously used a different solution; we used a bit of Talend and Wherescape Red.
What was our ROI?
I have seen a return on investment as it means we don't have to employ as many people; it's more about cost avoidance, but I have not removed employees.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing was simple enough.
What other advice do I have?
dbt is easy to use and easy to learn, but it has some limitations that I would love to see mitigated; however, in general, most of my engineers are happy using dbt.
My advice for others looking into using dbt is that it is good if you have an organization with engineers who prefer to code and get hands-on, but if you have teams of engineers who prefer a mouse-driven, drag-and-drop type, less technical coding environment, other tools might be more appropriate.
I rate dbt overall an eight 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?
Florelle M.
Streamlined Development and Reliable Data with Effortless DBT Orchestration
Reviewed on Nov 14, 2025
Review provided by G2
What do you like best about the product?
What I appreciated most was the elimination of duplicated code that used to be spread across various scripts. This change has significantly enhanced data reliability and now lets me implement business logic directly in pure SQL. I also value how much it accelerates development, and I find the orchestration and deployment with DBT to be exceptionally straightforward.
What do you dislike about the product?
I found the project management aspect challenging when dealing with hundreds of models, as the interface can at times be quite complicated.
What problems is the product solving and how is that benefiting you?
This tool has addressed our primary needs during the data transformation phase, enhancing data reliability and making development more efficient. It also acts as a central resource, ensuring that all teams use the same data management functions, even though it does have some shortcomings. Overall, DBT performs exceptionally well.
Mehdi N.
Efficient Data Management with Room for Documentation Improvement
Reviewed on Nov 05, 2025
Review provided by G2
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.
Bhupendra S.
dbt keeps our data models clean, consistent and version controlled
Reviewed on Nov 03, 2025
Review provided by G2
What do you like best about the product?
I use dbt every day to transform raw data in our warehouse into clean, analytics ready tables and my workflow typically begins in VS Code, where I write sql models, then push them to Git for version control and run them through dbt Cloud. And overall it has also made collaboration between our team members much easier because dbt makes the whole process much more simpler.
What do you dislike about the product?
It's challenging when one change throws an entire run off track and the error messages are at best, vague. I also feel the need to defend is the handiwork of my contributor to dbt cloud. I have also encountered the overly relaxed strucure and the resulting chaotic command and environment specific configurations.
What problems is the product solving and how is that benefiting you?
I can onboard people more easily, which has dramatically increased the usage of my warehouse and decreased my reliance on fragile, one off sql scripts and we have a whole team of analysts, engineers, and product working to have the same versioned models just building and ready for use.
Marissa M.
Powerful Features and Git Integration, but Error Messages Need Improvement
Reviewed on Oct 28, 2025
Review provided by G2
What do you like best about the product?
DBT provides valuable features for rapid software development, and what I appreciate most is its seamless integration with Git. Its modular design, which includes the ability to build reusable models, conduct code reviews, and generate automatic documentation, is excellent. Additionally, I am impressed by its capability to define and run quality tests, which further enhances the development process.
What do you dislike about the product?
When a DBT run fails, the error messages displayed in the terminal are quite generic. I find this frustrating because it means I have to spend extra time searching through the logs to figure out what went wrong.
What problems is the product solving and how is that benefiting you?
It solves many problems, especially in terms of data trust, and improves integration, The method runs seamlessly and speeds up processes. We went from hundreds of disorganized scripts to a logical and maintainable pipeline structure.