--- title: dbt Reviews meta_title: 'dbt Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 209 reviews by the users' company size, role or industry to find out how dbt works for a business like yours. aggregate_rating: rating_value: 4.7 review_count: 209 scale: '5' date_modified: '2026-07-17' parent_category: name: IT Infrastructure url: https://www.g2.com/categories/it-infrastructure --- # dbt Reviews **Vendor:** dbt Labs **Category:** [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) **Average Rating:** 4.7/5.0 **Total Reviews:** 209 ## About dbt dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. ## dbt Pros & Cons **What users like:** - Users love the **ease of use** of dbt, thanks to its clear structure, intuitive documentation, and seamless integration. (34 reviews) - Users value dbt for its **integration of software engineering best practices** , enhancing maintainability and collaboration in SQL transformations. (21 reviews) - Users value the **automation** features of dbt, significantly enhancing SQL code maintainability and transforming data workflows. (17 reviews) - Users value the **transformative power** of dbt, efficiently organizing and modeling data for actionable insights. (16 reviews) - Users value dbt for its **high data quality** , ensuring integrity and enhancing analytics workflows through modularization and documentation. (14 reviews) - Productivity Improvement (14 reviews) - Solution Efficiency (13 reviews) - Analytics (12 reviews) - Efficiency Improvement (12 reviews) - Users value the **seamless integrations** of dbt with various platforms, enhancing their modeling and transformation processes. (12 reviews) **What users dislike:** - Users face challenges with **limited functionality** in dbt due to rigid models and debugging difficulties, affecting project progress. (13 reviews) - Users often face **dependency issues** with dbt, leading to time-consuming troubleshooting and disruption in workflows. (12 reviews) - Users find the **steep learning curve** of mastering concepts like Jinja and Git to be quite challenging. (10 reviews) - Users struggle with **unhelpful error messages** in dbt, making troubleshooting difficult and frustrating. (9 reviews) - Users face **confusing error reporting** that complicates troubleshooting and hinders quick identification of issues. (9 reviews) - Users find the **complex setup** of dbt challenging, especially with confusing error messages and a steep learning curve. (8 reviews) - Debugging Issues (8 reviews) - Users find the **learning curve quite challenging** , particularly with advanced features and debugging complexities in dbt. (8 reviews) - Query Issues (8 reviews) - Technical Issues (8 reviews) ## dbt Reviews ### 1. DBT review **Rating:** 3.5/5.0 stars **Reviewed by:** Sangavi D. | Data Engineering, Mid-Market (51-1000 emp.) **Reviewed Date:** June 24, 2025 **What do you like best about dbt?** Using SQL queries, it is easy platform to transform the data. **What do you dislike about dbt?** For legacy system its is not useful for tranformation **What problems is dbt solving and how is that benefiting you?** Data transformation ### 2. DBT review **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** June 24, 2025 **What do you like best about dbt?** DBT is user friendly and helps keep our data reliable, updated and secure **What do you dislike about dbt?** Upgrading from core is really expensive without there being any significant differences besides number of users **What problems is dbt solving and how is that benefiting you?** DBT helps us build our models and keep them refreshed in our warehouse ### 3. Great experience with dbt **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** October 01, 2024 **What do you like best about dbt?** 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. **What do you dislike about dbt?** dbt should add more AI apacilities faster **What problems is dbt 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 ### 4. It's like seeing an old friend that you really liked but haven't seen for a while. **Rating:** 5.0/5.0 stars **Reviewed by:** 📈 Rho L. | Business Intelligence Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** January 18, 2024 **What do you like best about dbt?** At it's core, DBT aligns three technologies to deliver knowledge better: SQL, YAML, & Jinja. You can do a lot with just SQL and YAML. Adding in Jinja makes SQL feel a lot more like traditional development. I kinda missed that. It's like seeing an old friend that you really liked but haven't seen for a while. dbt is magic for transforming and modeling data. It's a platform that allows us to wrangle, shape, and organize the data to model the business. With the help of DBT, we can implement the principle of separation of concerns to organize and manage our transformations. One of the key tools DBT offers is Directed Acyclic Graphs (DAGs), maps that illustrate the path our data takes from source to the final destination. These maps illustrate the data transformation arc. We start with the source data, which is often messy and unrefined. We use DBT to perform a series of transformations, taking the data on a journey from a multiverse of chaos to a world of understanding. We clean the data, apply business rules, and ensure the data conforms to our business dimensional models. These models or core business logic serve as the foundation for reporting. As we progress along the transformation arc, our data starts to take shape. We can build data marts for specific business areas or functions. These data marts are built with our business dimensional models, ensuring that the data is structured in a way that supports efficient analysis and reporting. Reporting on top of our business dimensional models. With the data now organized and modeled in a meaningful way, we can unlock valuable insights and empower decision-makers with actionable information . . . at scale. We can slice and dice the data, apply filters, and drill down into specific dimensions to understand trends, patterns, and outliers. The reports we develop are consistent because they come from a single source of truth, the business dimensional model. **What do you dislike about dbt?** dbt requires a mindset change. You have to buy into how they think about modeling. It's opinionated. dbt is method-agnostic (data vallt, mesh, kimball). But structure matters and you need to spend some time to understand dbt's mindset around stricture. **What problems is dbt solving and how is that benefiting you?** Let me tell you about the state of our data. At the time, we didn’t know. That was the issue. It was a black box. Our data model was opaque with logic scattered all across the data stack. As we pick around the edges a picture starts to form. Imagine a dense, thorny briar patch, each thicket representing a tangled mess of information. That's how I see it—unruly, interlacing, and chaotic. Management has a different take. They call it "spaghetti," a swirling plate of tangled noodles. It’s actually not far from the truth. Each report fed directly from the source, the logic for each was self-contained and sometimes borrowed. ### 5. dbt makes it easier to onboarding analysts to good software engineering best practices **Rating:** 5.0/5.0 stars **Reviewed by:** Rulyan R. | Mid-Market (51-1000 emp.) **Reviewed Date:** January 04, 2024 **What do you like best about dbt?** Its easy to use even for newcomers and dbt also uses sql that is the most democratic language for data manipulation. From the start is very quick to integrate with your data stack in just a few clicks. I use dbt for for data transformation and data modelling every day and its many features like data lineage, version control, ci and slim ci, testes, documentation, model contracts make it easy to apply DataOps in you project **What do you dislike about dbt?** Its feature to model in python depends on the data plataform you are using. Its IDE still misses some of the functionalities that other IDE have that make development more easy, but new features are rolling out every new release of dbt cloud **What problems is dbt solving and how is that benefiting you?** We use dbt to make a data migration from an old stack to the modern data stack and its helping us develiver quality in our data that we didnt have in the legacy pipelines ### 6. Data Trasformazione to to enable Analytics Engineering **Rating:** 5.0/5.0 stars **Reviewed by:** Uddipan M. | Engineering Manager, Enterprise (> 1000 emp.) **Reviewed Date:** December 26, 2023 **What do you like best about dbt?** Easy to write transformation in SQL language augmented by Jinja templating techniques. Support of Python models is powerful. Good library of Open source Macros makes life easy for Analytics engineers. Write test cases to test model results,. Powerful documentation capabilities. Works very well with Snowflake. **What do you dislike about dbt?** To use DBT effectively, one needs to learn how to modularize SQL using CTEs. Bit advanced knowledge in SQl really helps. **What problems is dbt solving and how is that benefiting you?** Historically Analytics and data engineering teams worked seperatly, where analytics teams created a business logic and the engineeres implemented them without much context of the business. This process was time consuming and data engineers were overwhelmed. DBT solved that for our use case. Using DBT analytysts can write the business logic using plain SQL (A must have skill for analysts) , then engineers just use the DBT project to scale, optimize and deplot to production, Its a huge effort and time saver and enabled quick go to market with data insights. ### 7. A great environment and a powerful daily tool for Data Analysts and Engineers. **Rating:** 5.0/5.0 stars **Reviewed by:** Donovan M. | Mid-Market (51-1000 emp.) **Reviewed Date:** February 07, 2024 **What do you like best about dbt?** dbt Cloud - I recommend it to every org to get Data Analysts & Analytics engineers up and running quickly without having difficulty setting up during the onboarding. It's easier to adopt new teammates when they get to dive into the models immediately and add value sooner and solidify their grasp early. **What do you dislike about dbt?** I dislike navigating the logs in the Job Runs tab. The titles don't seem intuitive and the content could be more streamlined for finding faults. **What problems is dbt solving and how is that benefiting you?** Easy onboarding - streamlined development - the guided point-and-click adventure for github saves a ton of time and is probably the best in class solution I have seen for managing state. Please dont ever change this. dbt data modeling and test building is a fun experience on dbt cloud, my day to day work is fun because of dbt. Testing is super easy for pro-active data quality checks. I wish there was more visible ways to incorporate REACTIVE testing, like Metaplane's monitors, into dbt. DBT support was a bit slow here in Africa when the Github outage took place last year - some frustration around how slow responses were, how unclear processing was but I have personally learnt how to navigate these issues outside of dbt env. ### 8. Our analytics are more reliable and efficient **Rating:** 4.0/5.0 stars **Reviewed by:** Emily B. | Labor Law Specialist, Staffing and Recruiting, Mid-Market (51-1000 emp.) **Reviewed Date:** February 04, 2024 **What do you like best about dbt?** Im thrilled to e­xplore how dbt revolutionizes our work by de­lving deeply into the data world. Its a total game­changer providing remarkable simplicity in formulating and utilizing data code­ within our warehouse. When it come­s to version control dbt streamlines the­ entire process e­nsuring a smooth experience­ and maintaining crucial data models for analysis. **What do you dislike about dbt?** It would be good if dbt made it easier for new folks. It can do a lot with data stuff, but figuring how to set it up and use all its cool things can feel hard at first. More intuitive guides or a simpler way to learn the basics would make it nicer for people just starting with data changes. **What problems is dbt solving and how is that benefiting you?** In my role as a data manage­ment specialist, I have seen how dbt changed how we change data. It keeps changes same under control and tested well guaranteeing how exact our analyzing is. The automatic things of dbt have helped us work better freeing our team for strategic things not manual data work. This made us more quick and able to answer with data that helps our group make choices based on data. ### 9. Using dbt has improved accuracy and collaboration in our data projects **Rating:** 4.5/5.0 stars **Reviewed by:** Roland P. | Data specialist, Computer Networking, Small-Business (50 or fewer emp.) **Reviewed Date:** January 26, 2024 **What do you like best about dbt?** In my role I absolute­ly love using dbt - its the ultimate tool for transforming data with e­ase. It effortlessly inte­grates into our current systems making our analytics work a bre­eze. Were­ all in on dbt because it exce­ls at data transformation and organization boosting our efficiency and collaborative e­fforts tremendously. **What do you dislike about dbt?** It would be fantastic if dbt could e­nhance it's toolkit for visual data modeling. At prese­nt its heavily focused on coding but integrating a more­ visual approach to working with data would undoubtedly elevate­ its utility especially for individuals who gravitate towards graphical me­thods for data analysis. **What problems is dbt solving and how is that benefiting you?** As data enthusiasts we­ consider dbt our everyday supe­rpower dramatically enhancing our data analysis while e­ffortlessly managing complex data changes. Its our goto tool smoothing our data work and e­nsuring our insights are as sharp as a tack allowing us to make informed de­cisions to propel our business forward. ### 10. Transformation step of ETL/ELT pipelines made easy **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Insurance | Mid-Market (51-1000 emp.) **Reviewed Date:** January 17, 2024 **What do you like best about dbt?** Using DBT Cloud, the IDE is very intuitive, project lineage diagrams are very helpful. The general use of Jinja referencing and CTE's within the models made the flows very easy to follow, even with very large complex datasets that require lots of transformation. DBT integrates very easily with multiple ELT tools that we have used. Have all transformations in SQL form just makes everything easier. Being scheduled easily, we run multiple DBT pipelines daily. **What do you dislike about dbt?** With DBT Cloud you can only have one project per user without paying for a payed tier of the product, which is fair but makes for harder collaboration at this level. **What problems is dbt solving and how is that benefiting you?** Previous functions that were performed as adhoc scripts in python were made easy, running at a fraction of the time due to being rewritten in a significantly more efficient manner. Various functions across the business that require some sort of data transformation or manipulation, often previously manually were centralised all on one platform being DBT. Workflows and pipelines flowed more logically, and were scheduled and automated easily. Reports that are used daily by the business run quickly and very reliably. Tests and checks to validate data that was also previously done manually are all now integrated into the pipelines and automated, making multiple teams lives easier. ### 11. This is a versatile product that figures data-centric tasks by virtue of its robust features. **Rating:** 5.0/5.0 stars **Reviewed by:** Ismail I. | Small-Business (50 or fewer emp.) **Reviewed Date:** January 06, 2024 **What do you like best about dbt?** Having worked closely with data teams using dbt for the last year, I understand its benefits of a lightweight and version-friendly SQL work. This makes PG ideal for teams with multiple users because it simplifies code execution across different environments. Running functions in parallel leads to increased productivity, which is one of the most significant advantages. This is a versatile product that figures data-centric tasks by virtue of its robust features. The interface and usability of Dbt is commendable, making it very easy execute a complex data operation flow without any friction. **What do you dislike about dbt?** On the flip side its advanced functionality can sometimes be a case of good things never used. It is quite difficult to leverage the maximum capabilities of this language, especially when you have a very limited number of examples of syntax which kind of makes it feel like there is some creativity limit on it preventing one from properly dwelling deep into exploring what its core functions are. **What problems is dbt solving and how is that benefiting you?** Dbt has been a game changer in terms of how we process data. The benefit is that it eliminates manual repetition of tasks and controls process consistency in different stages. This has proven to be much more time-efficient as well as the data is simply more accurate – which directly supports improved project management goals. ### 12. Tool which provides simplified coding experience **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** January 05, 2024 **What do you like best about dbt?** I have been using dbt over more than a year now and I am using it almost every day as a data engineer. Its very simple to use and it is advantageous in many ways. It is easy to implement the code pipelines using dbt. The user interface is pretty good. Modularity and reusability is most useful feature. Also it is very useful in debugging with its code lineage feature. It is easy to integrate it with cloud data platforms such as Snowflake or Redshift. Also I have interacted with the support team from dbt for some of my doubts. I would recommend it to data architects to consider dbt in the modern data stack projects. **What do you dislike about dbt?** It would be better if we have column level lineage available in dbt. **What problems is dbt solving and how is that benefiting you?** dbt is solving the code lineage problem which is very difficult when we have a lots of SQL scripts. Also custom as well as user defined tests helps me in maintaining the data quality. This helps me in saving our teams precious time compared to time spent in solving defect or bug is raised by our reporting team. ### 13. Good tranformation tool for data engineers : Complete SQL Magic. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 24, 2024 **What do you like best about dbt?** DBT has been game changer in the realm of data analaytics for me. Its One of standout feature is abilty to transform data in warehouse itself it makes it lightning fast The powerfult modular sql based approach to define transformation makes it fall in love for data engineers. Its automatic document generation feature is simply outstanding. Its SQL based moduler approach makes it easy for implementation. **What do you dislike about dbt?** If someone is not well-versed in SQL it will be dificult to implement it initially. The main feature it doesnt have is inbuilt scheduler. The scheduler will make it complete transformation tool for data engineers. **What problems is dbt solving and how is that benefiting you?** Ability to create moduler, version control models ensures my transformation code is well maintanable and scalable. Its version control feature makes it very easy for developers to collabrate. Its feature of auto generating insights/ documents makes it outstand. ### 14. Dbt Cloud is exactly what a lean and mean team needs! **Rating:** 4.5/5.0 stars **Reviewed by:** Ran L. | Director of BI, Enterprise (> 1000 emp.) **Reviewed Date:** January 10, 2024 **What do you like best about dbt?** Pipeline execution management is easy! - Task dependancies are easy to manege - Excution logs are deatiled - Alerting is easy - Initial setup is super easy Convenient dev enviroment - The git integration enables to easily spin up development environemnts, check out a development branch and run you code in a production like environemnt **What do you dislike about dbt?** Would be nice to be able to set up several Snowflake connections for the same project. **What problems is dbt solving and how is that benefiting you?** It reduces the hassle and the overhead around data pipeline automations. Makes it easy to keep a lean and mean team, yet have everything you need for a production data pipeline ### 15. Transforming data with dbt **Rating:** 5.0/5.0 stars **Reviewed by:** Aniket T. | Software Developer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 19, 2024 **What do you like best about dbt?** dbt is an efficient solution that is capable of transforming raw data into important insights. I've been utilizing it for data transformation and it integrates easily with most of the elt tools. It has tons of features that enhances the development experience. **What do you dislike about dbt?** I've experienced issues when it comes to managing dependencies between models also realtime work isn't possible which is much needed. **What problems is dbt solving and how is that benefiting you?** dbt helps us in data quality checks and preparation before making it available for everyone. It ensures data accuracy and maintains regularity of the transformed data through automation testing. ### 16. One of the Best Data Transformation Tool **Rating:** 5.0/5.0 stars **Reviewed by:** Subhadip K. | Mid-Market (51-1000 emp.) **Reviewed Date:** September 07, 2023 **What do you like best about dbt?** I am using DBT more than 1 year. Since the first day I started using it I like it's many things: 1) Simplicity: It is very simple. We just need to write SELECT quries to achive the whole design. So after the development, 2) Version Control: DBT used to integrate with version control tool like GIT. So we can easily track the changes of it. 3) Materialization: With the help of the materialized, we can configure our model. We can create views, tables etc using it. 4) Documentation: In DBT we can create yml files to describe each of the models, columns and their usages and all. It will create very good DBT docs. 5) Data Lineage Graph: DBT automatically creates data lineage graph. It helps a lot to analyze and debug code. 6) Schedule: DBT has its inbuild scheduler, so very easily we can schedule dbt jobs. **What do you dislike about dbt?** dbt works in a batch mode. If we want to build a realtime job then it will not be possible in dbt. Although dbt is a data build tool. It do tranformation but it is not exactly a ETL tool where we can do data extraction, transformation and load. **What problems is dbt solving and how is that benefiting you?** 1) Simplicity: It is very simple. We just need to write SELECT quries to achive the whole design. So after the development, 2) Version Control: DBT used to integrate with version control tool like GIT. So we can easily track the changes of it. 3) Materialization: With the help of the materialized, we can configure our model. We can create views, tables etc using it. 4) Documentation: In DBT we can create yml files to describe each of the models, columns and their usages and all. It will create very good DBT docs. 5) Data Lineage Graph: DBT automatically creates data lineage graph. It helps a lot to analyze and debug code. 6) Schedule: DBT has its inbuild scheduler, so very easily we can schedule dbt jobs. ### 17. It was good **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Telecommunications | Mid-Market (51-1000 emp.) **Reviewed Date:** October 20, 2024 **What do you like best about dbt?** To build reliable data models quickly and collaboratively **What do you dislike about dbt?** It should be more accesible with more features **What problems is dbt solving and how is that benefiting you?** Problems related with Data visualizations and optimizations ### 18. Ease of working in a team **Rating:** 5.0/5.0 stars **Reviewed by:** Lucas Gabriel S. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 09, 2024 **What do you like best about dbt?** Transparency for everyone, with dbt the task of working on data as a team is made easier. We can apply different processes in our analysis thanks to the ease that dbt provides, application of tests, governance and observability. Even though it is not a tool specifically for this, it helps to apply dataops **What do you dislike about dbt?** Learning time, despite being quick to learn, requires time to better understand its features to speed up the development process **What problems is dbt solving and how is that benefiting you?** transparency over data transformation, managing to bring business people closer to the data ### 19. Excellent tool for data transformation **Rating:** 5.0/5.0 stars **Reviewed by:** Werleman T. | Business Intelligent Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** April 03, 2024 **What do you like best about dbt?** It has helped us transform our data and structure it better and its easy use **What do you dislike about dbt?** It should provide a tool to better enable model documentation. **What problems is dbt solving and how is that benefiting you?** We can have the data structured through code; This helps us when migrating data to any type of DWH. ### 20. DBT is a great tool that has saved our data team a lot of time. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Automotive | Mid-Market (51-1000 emp.) **Reviewed Date:** January 05, 2024 **What do you like best about dbt?** Model creation and CI/CD are top features. Thanks to DBT we have reduced the inconsistency of our data models and we reduced the number of manual tasks performed by the team. **What do you dislike about dbt?** The documenting process could be improved. Since we started using DBT, the load on our data warehouse has skyrocketed. Tools that optimize queries would be greatly appreciated. **What problems is dbt solving and how is that benefiting you?** We use DBT for data consolidation and transformation. DBT is a key piece of our data infrastructure. Every piece of information gathered from the different sources using fivetran is processed using DBT: from marketing events to information about our car's performance (we a car leasing company) ### 21. Awesome Experience with dbt Cloud App **Rating:** 5.0/5.0 stars **Reviewed by:** Rishi Y. | Small-Business (50 or fewer emp.) **Reviewed Date:** January 04, 2024 **What do you like best about dbt?** The App is continuously upgrading. It's becoming more user-friendly and bettering the user experience. SQL writing becoming very quick. **What do you dislike about dbt?** The customer support panel is always down. I have waited long many times for the help but it didn't arrive. **What problems is dbt solving and how is that benefiting you?** I designed the ETL pipeline to process healthcare data and build BI Dashboards on top of it. ### 22. Using dbt at work **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Automotive | Mid-Market (51-1000 emp.) **Reviewed Date:** January 12, 2024 **What do you like best about dbt?** The best thing about dbt is how easy is for you to load and transform the data using some built in features. They listen to the community's problems and always updating by adding packages and new features in order to make your life easier. **What do you dislike about dbt?** If there was any downside, dbt had already solved it by introducing new features and adapting to the problems that community have faced. **What problems is dbt solving and how is that benefiting you?** Introducing clarity to the business world by showing them (in business terms) all the inormation that they beed about data ### 23. Best opensource data orchestration tool **Rating:** 4.5/5.0 stars **Reviewed by:** Vinol D. | Head of Data, Mid-Market (51-1000 emp.) **Reviewed Date:** December 21, 2023 **What do you like best about dbt?** - Easy to use and deploy for someone with SQL background - Great community of support - Easy to launch and maintain - Can support data quality testing **What do you dislike about dbt?** - Complex transaofrmations which require python gets harder **What problems is dbt solving and how is that benefiting you?** - Ability to run data quality tests at scale and minimal costs - SQl tests easy to write and for ETL using SQL ### 24. dbt for data pipelines **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Enterprise (> 1000 emp.) **Reviewed Date:** August 29, 2023 **What do you like best about dbt?** dbt is excellent due to its wide use of macros and the ability to transform data using SQL, an analyst-friendly language. Given this we can train analysts to read dbt and understand the logic behind our data transformations, limiting the amount of work we need to do explaining data decisions or documenting logic. **What do you dislike about dbt?** I wish that dbt was more integrated with other data tools. It seems that a lot of data tools (fivetran, monte carlo, hightouch) are designed with dbt in mind but dbt never seems designed for these tools. It would be nice to have more accessibility within dbt, allowing us to create alerting and etl processes easier. **What problems is dbt solving and how is that benefiting you?** Dbt allows us to transform data using SQL and then run this data daily to provide fresh data to analysts. With this data we are able to make business decisions ultimately impacting our bottom line. We also use dbt for minor tests to make sure our data is accurate and clean. ### 25. Data Scientist **Rating:** 4.5/5.0 stars **Reviewed by:** Japjeet S. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** August 18, 2023 **What do you like best about dbt?** DBT is an easy to use too for anyone who knows SQL. Their IDE is wonderful and you can easily spin it up in no time. As a Data Scientist, doing modelling in DBT saves me hours of work and helps me provide an opportunity to others to focus on a more self serve analytics **What do you dislike about dbt?** DBT is a great tool but there are a few things missing from it. Direct connection to postgres SQL. Mixing of different sources and more convinent ways of build test and macros. **What problems is dbt solving and how is that benefiting you?** Dbt helps us build models for a lot of different complex queries that get used. DBT helps us compile massive queries into tables or views and helps with the flow. ### 26. An awesome tool for easy Data Transformations **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** October 07, 2023 **What do you like best about dbt?** One of the best things about dbt is that because it's an Sql-based platform, anyone ranging from a Data Analayst to a Data Engineer can easily implement and deploy Data Pipelines. It provides integrations with any different data sources like postgres, Snowflake, Bigquery etc along with features like CI/CD and version control. **What do you dislike about dbt?** Currently dbt only focuses on the transformation aspect of a data pipeline. It can also focus on Data quality. **What problems is dbt solving and how is that benefiting you?** dbt has enabled engineers to write a data pipeline in an SQL based format instead of writing huge codes using the same big data technologies, thus enabling anyone on the data team to setup and build their own pipelines. It also provides its own cloud platform where we can run those jobs and get data as per request. ### 27. Easy to use tool for building and managing data models! **Rating:** 5.0/5.0 stars **Reviewed by:** Dhruv B. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 04, 2024 **What do you like best about dbt?** Automatically created ERD diagrams and much more metadata about models built. **What do you dislike about dbt?** Updating versions can be time consuming and cumbersome. **What problems is dbt solving and how is that benefiting you?** It allows me to batch and process data querying elsewhere so users get to experience high performance datasets (queried on 100 million+ rows) ### 28. Dbt is all you need for your ETL processes. **Rating:** 5.0/5.0 stars **Reviewed by:** Aayushi P. | Senior Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 12, 2024 **What do you like best about dbt?** DBT is an all in one tool. You dont have to leave the plaform to get the things done in the right way. The readibility and code structure is very nice. **What do you dislike about dbt?** The documentation is not very extensive. **What problems is dbt solving and how is that benefiting you?** It helps me to do the following things- 1. Visualise the lineage 2. Continous integration 3. Run tests and view documentation 4. Run job schedules with ease 5. Help transform and move data between different sources ### 29. Overall great data transformation tool/framework **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** August 04, 2023 **What do you like best about dbt?** It brings best software development best practices to a world that didn't have them natively several years ago. It helps speed up the delivery of data transformation models and consumable data. It provides more than a data transformation framework, tests and documentation are two very welcome features to it. **What do you dislike about dbt?** Some people may have a hard time getting to know the framework; for this, the courses on the dbt website are a great introduction. For people coming from a traditional drag & drop (no code) tool, the change of mindset is even more challenging. There are no training materials for addressing the "this is how you did it with a traditional tool" and "this is how you do it with dbt", so these have to be created internally by each data team. **What problems is dbt solving and how is that benefiting you?** Time to deliver, data quality checks prior to making data available to users (data quality issues are detected by dbt and not by data consumers). Data documentation directly on dbt and propagated to our data catalog. Reusability of data models and less redundant code. ### 30. DBT: Streamlining Data Transformations with Suave and Panache **Rating:** 5.0/5.0 stars **Reviewed by:** Mikhail B. | Mid-Market (51-1000 emp.) **Reviewed Date:** May 17, 2023 **What do you like best about dbt?** Dbt has revolutionized the way we handle data transformations in our organization. It's incredibly easy to apply and use, even for non-technical team members. With its intuitive command-line interface and well-documented features, we were up and running in no time. One of the standout features of dbt is its ability to implement software best practices to our SQL codebase. It promotes modularization, version control, and testing, allowing us to treat our data transformations as a software project. This has significantly improved our code quality, collaboration, and overall data reliability. Top it with great, constantly growing, supportive community and a number of integrations with data observability and cataloging tools, third-party modules and libraries. Dbt is simply a great product. Its support for various data warehouses gives us the flexibility to work with our preferred platform, and the performance optimizations, such as incremental processing, have saved us valuable time and resources. I consider dbt a must-have for every data tech stack. It has streamlined our data pipeline development and maintenance, ensuring consistency and accuracy throughout our analytics models. Whether you're a data analyst, engineer, or scientist, dbt empowers you to transform raw data into valuable insights with ease. In fact, i was headhunted and hired for my current role, primarily because of my dbt knowledge. Dbt has exceeded my expectations on all fronts since day one and keeps doing it as it develops, it has become a number one tool in my professional armamentarium. Its simplicity, adherence to software best practices, and overall functionality make it a standout choice for anyone working with data. **What do you dislike about dbt?** Nothing, that is truly a great tool, created by a great team. **What problems is dbt solving and how is that benefiting you?** 1. Data reliability: Dbt helps ensure the accuracy and consistency of transformed data. It allows to define and enforce tests, perform data validation, and catch errors early in the pipeline. 2. Increased productivity: With dbt, i can work more efficiently by leveraging its modularization (macros and jinja templating), codebase management which leads to faster iterations and shorter development cycles. 3. Foster collaboration: dbt encourages collaboration among data practitioners by providing version control support. This enables seamless collaboration, change tracking, and simplifies the process of reviewing, merging, and rolling back changes. 4.Optimize performance: dbt incorporates performance optimization such as incremental processing. Dbt allows me to work smarter and faster, build scalable pipelines, create high quality code that is easy to maintain. ### 31. DBT is best data modelling tool **Rating:** 5.0/5.0 stars **Reviewed by:** Shubham K. | Mid-Market (51-1000 emp.) **Reviewed Date:** December 23, 2023 **What do you like best about dbt?** Cross Referencing of models, Macros and custom functions **What do you dislike about dbt?** Error Messaging and no cross-query functionality **What problems is dbt solving and how is that benefiting you?** We have built our organization's data stack using dbt and also we have connected dbt models to BQ which in turn feeds tableau dashboards ### 32. Making data transformations easier **Rating:** 5.0/5.0 stars **Reviewed by:** Onkar N. | Associate Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** February 09, 2024 **What do you like best about dbt?** Its simplicity and focus on transforming data in a reproducible and maintainable way. **What do you dislike about dbt?** Sometimes,its learing curve can be steep for beginners and managing comples transformation might require advanced knowledge. **What problems is dbt solving and how is that benefiting you?** dbt simplifies data transformation making analytics pipelines easier to manage and more reliable,which benefifits users by stramling workflows and improving efficiency. ### 33. so usefull **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 24, 2024 **What do you like best about dbt?** 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 dbt?** 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 dbt solving and how is that benefiting you?** It provides standardize transformation process that help in less error, version control is also a good feature ### 34. DBT, the unified codegen of downstream model heterogeneous complexity **Rating:** 5.0/5.0 stars **Reviewed by:** David L. | Senior Solutions Architect, Enterprise (> 1000 emp.) **Reviewed Date:** April 29, 2023 **What do you like best about dbt?** DBT creates a new SQL-like syntax, use select statement and configuration file and headers to control behavior, make data model task more reliable and readable. Easy for data analysis with existing basic SQL knowledge. **What do you dislike about dbt?** We can rarely go through all features in dbt, since it is too much Solutions are sometime duplicated. You can always find 2-4 ways to fulfill one purpose, and it can overwrite with each other. DBT integration with CI/CD is not easy, even in DBT cloud since file is the first citizen in dbt world. You can only have them tested in dbt project, even for only unit tests. **What problems is dbt solving and how is that benefiting you?** data modeling and materialization. One of a customer is migrating their data warehouse to bigQuery. After platform and data migration, they think adopting new data modeling tool on new platform, DBT fit that gap and then is selected as standard ### 35. DBT **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Small-Business (50 or fewer emp.) **Reviewed Date:** January 04, 2024 **What do you like best about dbt?** Cloud.dbt has proven to be an invaluable tool for our data modeling and analytics needs. Its seamless integration with cloud platforms, user-friendly interface, and robust features have significantly streamlined our workflow. The platform's automation capabilities have allowed our team to focus more on deriving insights from data rather than dealing with intricate modeling processes. The collaborative environment enhances team productivity, making it a standout solution for organizations aiming to elevate their data analytics game. I use it daily. **What do you dislike about dbt?** Remember me during sign in doesn't work. **What problems is dbt solving and how is that benefiting you?** Automation of jobs and syncing with database ### 36. Best in class ELT **Rating:** 5.0/5.0 stars **Reviewed by:** Vinod B. | Data Warehouse Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 11, 2023 **What do you like best about dbt?** Best in-class SQLCentric tool providing ELT, orchestration with Lineage on the models. Make the development much easier and help to concentrate more on the Business. **What do you dislike about dbt?** DBT only supports SQL and Python models for now, and being an ELT, reading from external sources will not be possible, which makes DBT very constrained and the libraries quite limited. **What problems is dbt solving and how is that benefiting you?** A powerful tool in providing powerful business solutions. We are using Databricks on DBT which supports delta formats and Macro is the best option to reduce repeated code. ### 37. DBT - easy transformation tool **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Mid-Market (51-1000 emp.) **Reviewed Date:** May 03, 2024 **What do you like best about dbt?** Can perform transformation using SQL statement. Very easy to perform **What do you dislike about dbt?** Nothing much......simple and easy to use **What problems is dbt solving and how is that benefiting you?** ELT tool which helps to perform transformation using SQL and create pipelines. ### 38. MetricFlow **Rating:** 5.0/5.0 stars **Reviewed by:** Praveen K. | QA Engineer, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** August 12, 2023 **What do you like best about dbt?** I like the most in MetricFlow is, it will simplify the code governance with autogenerated SQL. It will pull metrics into downstream applications.And also i like the UI most. **What do you dislike about dbt?** Need to introduce more new interesting features in frequent releases.Should increate support of the application as well.Also better to support new intergrations. **What problems is dbt solving and how is that benefiting you?** Please add new and more interesting features to make our work easier and quicker. Add more integrations in MetricFlow for better productivity. ### 39. dbt adds so many features to SQL that I hadn't even realised were missing **Rating:** 4.5/5.0 stars **Reviewed by:** Stuart C. | Senior Data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** December 12, 2022 **What do you like best about dbt?** There's a lot that I really like about dbt, particularly in the way it automates so much of the 'grunt work' out of transforming data. It's now tough to imagine how we handled refreshing our data warehouse before dbt! Specifically I am a fan of how dbt: - Works out dependencies rather than you having to stay on top of which models need to be run before others - Automates testing, running tests on a schedule rather than when you remember to run the testing! - Handles version control, allowing you to keep track of changes - Provides a straightforward way of handling separate development and production environments, so you can see the impact of your changes before making them live - Has a very active community of Slack users and package developers **What do you dislike about dbt?** This is quite minor, but with documentation it can be a bit onerous to keep .yml files up to date, as the formatting needs to be exact and it is not always obvious when something is wrong, for example, with the amount of tab spacing. **What problems is dbt solving and how is that benefiting you?** dbt has essentially "automated the boring stuff", letting us spend less time on boilerplate SQL work and more time thinking about the design of our models and how they best serve our reporting needs. ### 40. dbt is currently the software I love most **Rating:** 5.0/5.0 stars **Reviewed by:** Joseph T. | Data consultant, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt improves every facet of SQL transforms for analytics. My favorite features in order: --Isolate each piece of business logic to a single model, ensuring that everything downstream inherits that definition. --Build canonical fact tables, then combine those into report-ready aggregate marts. Once the fact tables are built, the time-to-data-mart is so fast. --Automated testing for code and data quality --Import code packages, either open source or private --Managed interactive documentation **What do you dislike about dbt?** The cloud IDE is still very much a work in progress. Already better than using a local IDE, but there are still enough quirks and bugs to be frustrating. Setting up a new project seems overly onerous--the same score of steps have to be done the same way, which seems like it could be just a copy/paste from a different project. Most implementations probably only have one project going, though, so that's a pain only us agency types feel. **What problems is dbt solving and how is that benefiting you?** SQL transforms with daily code runs. Deploying packaged code across multiple projects. Monitoring code and data quality through daily automated testing. Prepare raw data for business user consumption. ### 41. The Only Analytics Engineering Toolkit You Need! **Rating:** 5.0/5.0 stars **Reviewed by:** Frank S. | Data Analyst, Data Protection Officer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt makes it very simple to plan, construct, and continuously transform our company data on regular intervals in order to power our decisions on product design, user experience, and much more. Moreover, its Slack community will not let you fail and is incredibly helpful. **What do you dislike about dbt?** The fact that dbt is constantly expanding what you can transform and helping you to code those transformations makes it a hard software to not be married to. Marriage to a software is often the death of an operating budget over time, but the value is incredible with dbt. **What problems is dbt solving and how is that benefiting you?** dbt provides a cloud-based job-running environment that I can set and forget, an integrated development environment to code my SQL and Python transformations in, and a way to easily deploy automated testing of my code to ensure data quality and reliability. Moreover, dbt makes it easy to write your code with native format assistance (SQLFMT), active syntax recommendations, shortcuts, and a suite of learning videos and docs. ### 42. Game changing solution that brings software engineering best practices to data work **Rating:** 5.0/5.0 stars **Reviewed by:** Max L. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt brings a ton of best practices from software engineering: code versioning, automated testing, documentation, and support for deploying to multiple environments to the process of transforming data (ETL/ELT). Prior to using dbt I'd either have SQL code stuck in an IDE somewhere or obfuscated through an orchestration tool like airflow that made it difficult for non-coders to contribute effectively to a data team. Even as a senior data engineer I love the best practices and simplicity that dbt has brought to my team and I'm looking forward to its continued growth! **What do you dislike about dbt?** Nothing major, dbt is still a relatively new product with active development so some minor annoying things are constantly being improved. For example, the IDE in dbt cloud wasn't super performant and auto-completion would not always work, but both things were improved drastically through the most recent release. We had a little bit of an initial learning curve for customizing our environment to suit our specific use-case, but I like that we weren't forced to do a bunch of customization out of the box so you could easily start using the product. **What problems is dbt solving and how is that benefiting you?** Performing data transformation at scale using only SQL and deploying those to multiple environments while using code versioning. Our ability to create standardized reporting tables for multiple different projects has drastically improved. ### 43. Analytics Engineering revolution! **Rating:** 4.5/5.0 stars **Reviewed by:** Maria S. | Data Platform Engineering Lead, Enterprise (> 1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt is a potent tool with lots to explore. The data lineage is fantastic, where you can easily see if a small change brakes a model downstream. Tests are integrated into it, which we use a lot, specially custom ones. Macros are handy and fantastic resources for controlling tests, functions, environment behaviour, etc. Building new models is effortless because the analyst only needs knowledge of SQL (and a bit of dbt but like any tool). Finally, I love the dbt community spirit, the excellent documentation and how dbt is continuously improved. **What do you dislike about dbt?** However, I am worried about the scalability of using one repository. There were two of us when we started using dbt, but we are +10 now and this reflects in running times, release management and CI/CD. We would love to see a bit more support on this. Another thing is the alerting system, we can set up tests as warnings, but you need to enter dbt cloud on purpose and see the alerts inside the job. We are building alerts out of the box because this doesn't work for us. Lastly, it was difficult for me initially to adapt from the "old" data stack, but I am 100% dbt converted now. **What problems is dbt solving and how is that benefiting you?** We previously had an ETL tool which was very difficult to maintain and contribute to. This was a huge bottleneck, and dbt has allowed many people to contribute to modelling and building dashboards. ### 44. dbt has vastly improved how I get work done. It has changed the data industry and it's wonderful **Rating:** 5.0/5.0 stars **Reviewed by:** Connor S. | Analytics Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt gives data teams the ability to version their SQL code, execute that code as often as they'd like, maintain different environments and support multiple users in parallel. All of which require barely any thought from the user. All these functions used to be major pieces of my daily work and with dbt, they are simply memories of when I set up the product. It's wonderful. **What do you dislike about dbt?** Once you start getting into some of the advanced functionality of dbt, you can find yourself in what feels like unexplored land. It's an open-source product, so your own creativity is your only limit. However, in those situations finding syntax examples for anything that isn't a main function of dbt is going to be extremely challenging. **What problems is dbt solving and how is that benefiting you?** They're constantly improving the UI and user experience in ways that enable my teammates who may have less experience with technical or database maintenance work, to take ownership of their own work projects and exceed. ### 45. Efficient, easy to use and reliable for development **Rating:** 4.5/5.0 stars **Reviewed by:** Alex G. | Junior Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** December 14, 2022 **What do you like best about dbt?** Fast development times and ease of use are my two favourite qualities of dbt. It allows our team to build and test new sql models very quickly, and even less experienced team members with basic knowledge of sql are able to contribute. **What do you dislike about dbt?** With large complex models tracking column lineage can be tricky. Especially as fields go through many layers of transformations, identifying where certain data quality issues are arising can be challenging. I realise this is not an easy problem to solve but column level lineage would be super useful at speeding this process up. **What problems is dbt solving and how is that benefiting you?** The fast dev times allow us to efficiently accommodate business changes into the logic of our data transformations. As a relatively small data team of 8 serving an org of 600, keeping up with changes to the business is vital for us to be able to work on other high-value data projects. ### 46. dbt has fundamentally changed the way we work **Rating:** 5.0/5.0 stars **Reviewed by:** John P. | Senior Manager - Analytics Engineering, Mid-Market (51-1000 emp.) **Reviewed Date:** December 06, 2022 **What do you like best about dbt?** dbt has enabled us to literally re-model a data warehouse from scratch in a matter of months. All the complexities of handling scheduling dependencies, lineage, incremental models, snapshots, and robust, thorough testing have been abstracted away freeing us up to focus on the modelling and design work. If we had built all these ourselves this would have been a years-long project. dbt has also empowered our analysts to build data products without the need for BI Engineers. **What do you dislike about dbt?** The primary downside we've all come to experience is that once you've worked with dbt you'll never want to work in an environment that doesn't transform its data with dbt. **What problems is dbt solving and how is that benefiting you?** dbt really solved the problem of being able to build a world-class data warehouse rapidly with a small team of analytics engineers. The benefits have been numerous, from having jobs run according to dependencies so we don't have to worry about timing or manually schedule tasks, to built-in testing which means we know about errors before the business does. Our development times are now a fraction of what they were, and the analysts love that they are no longer dependent on a team of data/BI engineers to build and maintain their own models. ### 47. Where has dbt been for the last 10 years? **Rating:** 5.0/5.0 stars **Reviewed by:** Matthew K. | Vice President, Data Strategy & Analytics, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** I've been an analytics professional working in databases for the last 10 years. dbt solves a large number of the problems I've encountered deploying code (be it often repeated analyses, reporting, or clinical rules) in a repeatable scalable way. dbt handles the repeatable processing and provides easy-to-consume documentation to share with others, so that I don't have to replicate the logic in separate documentation artifacts. **What do you dislike about dbt?** Because of its youth, many highly-valuable features are distributed as add-on packages. It requires a significant commitment to understand the landscape of commonly used add-ons that are pervasive throughout the community. Looking forward to more highly-valuable functionality being built into the core software! **What problems is dbt solving and how is that benefiting you?** dbt allows my organization to upskill our analytics professionals. The teams that own and use the key business logic can directly deploy updates and additions into our common warehouse environment and begin to use and share it quickly. ### 48. Powerful and Easy to Use ETL Tool **Rating:** 5.0/5.0 stars **Reviewed by:** Don A. | Director of Research and Development, Small-Business (50 or fewer emp.) **Reviewed Date:** December 12, 2022 **What do you like best about dbt?** The best part of DBT is the power that comes with its ease of use. Once you play around with DBT a bit and get a handle on it, it can do all sorts of great tricks with just a SELECT statement and a little bit of Jinja. **What do you dislike about dbt?** DBTs only weakness right now is I find the examples in the documentation to be a little simplistic, not covering all the options like the examples in a Microsoft help page would. Luckily, for more complicated use cases, you can get help in their Slack community, which is quite lively and helpful. **What problems is dbt solving and how is that benefiting you?** DBT is helping us normalize several data sources together into one master model and then exposing slices of that master model in the form of views we base our exports on. We have over 2k models between putting the sources together and then sharing the slices. ### 49. Amazing Product We Have Used for Years **Rating:** 5.0/5.0 stars **Reviewed by:** James R. | Sr Director of Data and Insights, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** DBT allows us to transform our data in a way that is easy to learn (with a sql background), easily adjustable, and incredibly powerful. Every dataset that is used by a business user at our company goes through DBT one way or another, some as simple as cleaning up some fields and names, and other through complex algorithms. **What do you dislike about dbt?** The code first style can be a little daunting to teach to newer people who have never seen a tool like this before or do not know SQL. I think the investment in teaching SQL/DBT is well worth the value provided. **What problems is dbt solving and how is that benefiting you?** We have dozens of datasets that come in in many different formats and levels of cleanliness. DBT allows us to take any dataset and convert it in a clean, scalable way into datasets that are easy to use for analystics and process automation ### 50. If you're doing analytics, you need dbt **Rating:** 5.0/5.0 stars **Reviewed by:** Adam M. | Head of AI and Data, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt was easy to integrate into our stack, and immediately began adding value. dbt has levelled up our data practice and helps to ensure that we're shipping reliable, consistent and accurate tables to our stakeholders. It allow for repeatability so that stakeholders don't need to know sql to use a useful table. **What do you dislike about dbt?** If you have multiple projects in your warehouse (BigQuery) in our case, you have to set up dbt for each. It would be ideal if, within BQ, we could consolidate projects somehow - although given security permissions, potentially not possible or practical. **What problems is dbt solving and how is that benefiting you?** Previously were modelling tables in our warehouse or BI layer leading to a lot of confusion and breaks in data. Using dbt, we can easily (i) enforce PRs for any new tables, (ii) enforce tests, (iii) leverage macros and (iv) define documentation. ## dbt Discussions - [What is DBT data Modelling?](https://www.g2.com/discussions/what-is-dbt-data-modelling) - 2 comments - [What is DBT technology?](https://www.g2.com/discussions/what-is-dbt-technology) - 2 comments - [What is DBT database tool?](https://www.g2.com/discussions/what-is-dbt-database-tool) - 1 comment - [What is DBT tool used for?](https://www.g2.com/discussions/what-is-dbt-tool-used-for) - 2 comments - [View dbt pricing details and edition comparison](https://www.g2.com/products/dbt/reviews?page=2§ion=pricing&secure%5Bexpires_at%5D=2026-07-19+01%3A50%3A57+-0500&secure%5Bsession_id%5D=f26f9fbc-2bbd-4150-85df-33164bf88302&secure%5Btoken%5D=7364fac6391136a7622b4f0362c43403cf923feb09d6a774c919c5fbd37214c9&format=llm_user) ## dbt Integrations - [Amazon EC2](https://www.g2.com/products/amazon-ec2/reviews) - [Apache Airflow](https://www.g2.com/products/apache-airflow/reviews) - [Azure Databricks](https://www.g2.com/products/azure-databricks/reviews) - [Fivetran](https://www.g2.com/products/fivetran/reviews) - [GitHub](https://www.g2.com/products/github/reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) - [PostgreSQL](https://www.g2.com/products/postgresql/reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - [Spark](https://www.g2.com/products/apache-spark/reviews) ## dbt Features **Reports** - Reports Interface - Steps to Answer - Graphs and Charts - Score Cards - Dashboards **Data Source Access** - Breadth of Data Sources - Ease of Data Connectivity - API Connectivity **Management** - Auditing **Data Management** - Data Integration - Metadata - Self-service - Automated workflows **Automation** - Workflow Automation - Multi-platform support - Data Management **Agentic AI - DataOps Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Decision Making **Deployment & Integration - Semantic Layer Tools** - Multi-Environment & Multi-Cloud Support - Open API & SDK Integration **Data Transformation** - Real-Time Analytics - Data Querying **Data Interaction** - Profiling and Classification - Metadata Management - Data Modeling - Data Joining - Data Blending - Data Quality and Cleansing - Data Sharing - Data Governance **Functionality** - Transformation - Automation - Scalability **Analytics** - Analytics capabilities - Dasboard visualizations **Functionality** - Documentation management - Platform support - Template functionality **Data Connectivity & Federation - Semantic Layer Tools** - Cross-Source Query Federation - Dynamic Schema & Metadata Adaptation **Data Exporting** - Breadth of Integrations - Ease of Integrations - Data Workflows **Monitoring and Management** - Data Observability - Testing capabilities **Administration** - Error Alerts - Service Automation - Workflow management **Data Modeling & Metrics - Semantic Layer Tools** - Derived & Calculated Metrics - Time Intelligence Functions **Connectivity** - Hadoop Integration - Spark Integration - Multi-Source Analysis - Data Lake **Functionality** - Identification - Correction - Normalization - Preventative Cleaning - Data Matching **Cloud Deployment** - Hybrid cloud support - Cloud migration capabilities **Generative AI** - AI Text Generation **Agentic AI - Data Warehouse Automation** - Proactive Assistance **Performance Optimization - Semantic Layer Tools** - Query Caching & Acceleration - Adaptive Query Optimization **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling **Operations** - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks **Management** - Reporting - Automation - Quality Audits - Dashboard - Governance **Generative AI** - AI Text Generation - AI Text Summarization **Governance - Semantic Layer Tools** - AI Governance & Observability - Metric Lineage for AI Training Data - Version Control & Change Impact Analysis **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services **Generative AI** - AI Text Generation - AI Text Summarization **Advanced Intelligence - Semantic Layer Tools** - Natural Language Query Interface - Semantic Layer for AI/ML Models - Recommendation Engine **Agentic AI Enablement - Semantic Layer Tools** - Agentic Query Orchestration - Contextual Reasoning Layer - Workflow Automation via Semantic Agents **Building Reports** - Data Transformation - Data Modeling - Integration APIs **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications ## Top dbt Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (1,321 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (845 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,144 reviews)