--- 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: '2026-08-10' parent_category: name: IT Infrastructure url: https://www.g2.com/categories/it-infrastructure --- # dbt Reviews **Vendor:** Fivetran **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. A Developer Friendly Transformation Tool **Rating:** 4.0/5.0 stars **Reviewed by:** Syed A. | Data Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** February 03, 2026 **What do you like best about dbt?** I like best about dbt is how it brings a clean, developer‑friendly structure to analytics work. It makes modeling and transforming data feel organized and predictable, thanks to its simple SQL‑first approach and clear project layout. I also really appreciate how dbt encourages good engineering practices such as version control, testing, documentation. So the entire workflow becomes more reliable and collaborative. **What do you dislike about dbt?** I dislike about dbt is that some parts of the workflow can feel a bit inflexible, especially when you're trying to customize how tests or models behave in more complex projects. It also relies heavily on command‑line and configuration files, which can become demanding as the project grows. On top of that, dbt doesn’t handle ingestion or real‑time needs, so user often need additional tools to complete the pipeline, which makes the setup feel less seamless. **What problems is dbt solving and how is that benefiting you?** dbt solves the problem of scattered, inconsistent transformation logic by giving user a clean, structured way to manage SQL models, tests, and documentation in one place. I no longer needs to deal with random queries or unclear business rules, everything becomes version‑controlled and easy to trace. Which helps me in my workflows to become productive. ### 2. Versatile Data Transformation Tool **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about dbt?** I primarily value how dbt shifts data transformation into a software engineering workflow. By materializing code into tables and views automatically, it lets our team focus on the transformation logic rather than DDL boilerplate. The model selection syntax is incredibly efficient for running specific segments of our DAG without wasting warehouse resources. Macros and Jinja integration have also been game-changers for modularizing our logic and reducing code repetition. I find the YAML-based unit testing to be a robust way to ensure data integrity before it reaches our BI layer. Between the two, I prefer dbt Cloud over Core because the IDE provides immediate visibility into query results and schema changes, which speeds up our development cycle. I use it every workday. Customer support was quick and responsive when I ran into issues during the initial setup of dbt with Snowflake authentication. Implementation was also straightforward when connecting it to Snowflake, and once the connection was established, I didn’t have any ongoing issues aside from needing to reauthenticate every day. **What do you dislike about dbt?** The most significant friction point is the authentication lifecycle with Snowflake. The session tokens expire frequently (often every few hours), forcing a manual re-authentication process that disrupts the flow of development. Additionally, there is a noticeable feature gap between the versions. dbt Core lacks the native, instant result-set previewing that makes dbt Cloud so productive. Bringing a similar "live preview" or integrated results pane to the Core CLI experience would make it a much more viable option for local development. **What problems is dbt solving and how is that benefiting you?** We use dbt to manage the entire T (Transform) layer of our ELT process within Snowflake. Before dbt, our transformations were often opaque and difficult to test. Now, we have: Dryer Code: Macros help us maintain a "Don't Repeat Yourself" philosophy across hundreds of models. Improved Data Quality: By implementing automated tests on primary keys and relationship constraints, we catch upstream data issues before they impact stakeholders. Faster Onboarding: The combination of dbt Cloud’s UI and the structured project documentation makes it much easier for new analysts to understand our data lineage. ### 3. DBT has absorbed all the stress while making my life a lot easier **Rating:** 4.0/5.0 stars **Reviewed by:** Andrew S. | Business Development Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2025 **What do you like best about dbt?** I threw terabytes at DBT and expected the infrastructure to fail but DBT ran the distributed execution on its own with no intervention by me. The ability to run machine learning directly within SQL is strange but better than exporting to vertex.ai and dealing with cluster management myself. I also do not have to worry about cluster management as I can just write the query and wait for the results which in my opinion is very straightforward thing to do. **What do you dislike about dbt?** Billing is a trap as well as if you run a generic query without a filter the costs jump up right away which can be very annoying. I had to re-write all of my stored procedures because the syntax isn't quite like pl/sql. And I really dislike reading the logs when a model fails and/or errors occur. **What problems is dbt solving and how is that benefiting you?** DBT takes care of managing the server and I never had to manage it myself and also I used to have to sit around waiting for hours for my ETL to finish but with DBT now they complete really quickly. We just throw the dirty data into DBT and it will handle separating out the different types of storage without me worrying about it. ### 4. Reliable transformation practices at scale **Rating:** 4.0/5.0 stars **Reviewed by:** Scott J. | Manager, data engineering and analytics, Logistics and Supply Chain, Small-Business (50 or fewer emp.) **Reviewed Date:** January 26, 2026 **What do you like best about dbt?** One thing that I find impressive about dbt is that it promotes discipline in writing of transformations. It transformed my approach towards the way I deal with my work, as I now think twice before imposing changes. I use it on a regular basis, and it has enhanced teamwork since logic has less difficulty in reviewing and discussion. This has saved time on quick fixes and has assisted us in developing more confidence on outputs that may be shared. **What do you dislike about dbt?** What I do not like about dbt is that there is a huge effect of little errors in the models. Some of them may break down under the pressure of having a few downstream pieces broken when there is a slight change. It is time consuming and can even bring several individuals into the same problem when it comes to debugging those chains. In my case, this retards progress and results in context switching which can be annoying when time lines are near. **What problems is dbt solving and how is that benefiting you?** Dbt eliminates the issue of vague ownership and reasoning. It provides organization where responsibilities are clearly seen which enhances cooperation. In my case, it implies a reduced number of handoff problems and a streamlined collaboration. Co-workers become bolder in changes and tasks are less responsive on a daily basis. It has simplified our working process and made it more predictable in general. ### 5. dbt keeps our data models clean, consistent and version controlled **Rating:** 4.0/5.0 stars **Reviewed by:** Bhupendra S. | Senior Team lead, Mid-Market (51-1000 emp.) **Reviewed Date:** November 03, 2025 **What do you like best about dbt?** 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 dbt?** 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 dbt 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. ### 6. Makes Transforming and Managing Data Models Way More Manageable **Rating:** 4.0/5.0 stars **Reviewed by:** Alexander V. | DevOps Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** October 12, 2025 **What do you like best about dbt?** Thanks to dbt, I no longer have to depend on the engineering team to manage and transform the SQL data within our warehouse. It is the first step for me in organizing, testing, and documenting the entirety of our data models. I appreciate that all of this information is in one place in version control. I can track all changes made and the details surrounding each one. **What do you dislike about dbt?** Troubleshooting complex dependencies and build errors can be a daunting task. There are occasions when a model fails and it is unclear which upstream change might be the cause. While the documentation is really good, I have found digging into a Stack Overflow or Slack thread to be the answer for some of the more obscure problems. I also find the visualization of lineage in dbt Cloud to be cumbersome. **What problems is dbt solving and how is that benefiting you?** Data transformations are far more efficient now with dbt. I no longer need to create custom scripts or deal with disorganized SQL in dashboards, as I can now have a single layer that is testable and maintained for all my transformations. It is quick and dependable to run models in dbt Cloud, which assures me that the data is consistent and current for our business teams. ### 7. I can manage my own dependencies using dbt. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 10, 2025 **What do you like best about dbt?** dbt runs well on Redshift, since that is what was mentioned over and over again in the notes; however, dbt simply compiles the SQL and the warehouse itself handles the heavy lifting. Using Git and Version Control for Data Models, is nice because it keeps the data model from exploding. dbt also integrates with our AWS infrastructure without requiring tears. The speed is sufficient, as it simply passes the work to the database; although, having the transformation logic in one location is helpful. **What do you dislike about dbt?** The cost is becoming increasingly expensive and considering dbt is essentially a fancy SQL Compiler. dbt also has poor performance when handling un-structured data (although this may be due to Redshift); I'm unsure, everything seems to blend together. Additionally, the learning curve is very steep if you are not familiar with Jinja and setting-up YAML files properly. **What problems is dbt solving and how is that benefiting you?** dbt allows us to scale the analytics engineering work so we are not running ad-hoc SQL scripts on a laptop. dbt separates the compute and storage logic, allowing us to define the "what", while it determines the "how". dbt automatically manages the dependency graphs, which is great, as I cannot handle tracking those manually. ### 8. Efficient Data Management with Room for Documentation Improvement **Rating:** 3.5/5.0 stars **Reviewed by:** Mehdi N. | Data Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 04, 2025 **What do you like best about dbt?** 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 dbt?** 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 dbt 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. ### 9. Reliable data project workflow **Rating:** 4.0/5.0 stars **Reviewed by:** Elia M. | Data transformation engineer, Accounting, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2025 **What do you like best about dbt?** What I like about dbt most is that my modeling work is much more comfortable. I spend my entire time modifying logic or verifying the changes and the set of features is what I actually need. I operate it with Snowflake, and that integration ensures that my updates are regular. The installation was relatively fast and the number of times the tool has been used demonstrates the extent to which it has come to my rescue in order to maintain projects and ensure they are well organized. **What do you dislike about dbt?** The thing I do not like is that there are some spots that do not provide me with the flexibility that I need when I work on large portions of work. It imposes additional procedures which disrupt my rhythm. These weak spots are visible since I am in dbt so many times. There is a good response of the customer support but still the restrictions influence my speed during peak weeks. **What problems is dbt solving and how is that benefiting you?** Dbt addresses our problem of disorganized model upkeep in the team. I apply it in my daily activities keeping track of the changes and updating and ensuring that all goes in the right direction. The size of the features suits very well into our workflow and the frequency of use demonstrates how much easier our process is now. It has assisted us in preventing the instances of miscommunication and enabled all of us to be more certain of the work we drive forward. ### 10. Great UI Makes Data Lineage and Flow Easy to Understand **Rating:** 4.0/5.0 stars **Reviewed by:** Aneesh T. | Associate Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2026 **What do you like best about dbt?** Great UI—it's easy to see the lineage and the data flow. **What do you dislike about dbt?** Lineage isn’t exactly easy to follow when it’s rendered. I wish there were a better explorer so I could view the lineage properly. **What problems is dbt solving and how is that benefiting you?** dbt is our primary data transformation tool, it is helping us model data to out needs ### 11. Reliable Data Automation and Trustworthy KPIs **Rating:** 4.0/5.0 stars **Reviewed by:** Mohamed A. | General Management, Small-Business (50 or fewer emp.) **Reviewed Date:** December 15, 2025 **What do you like best about dbt?** What I appreciated most about DBT was its capability to automate the creation of form data models, allowing me to trust the data. I felt confident that the KPIs displayed were accurate, thanks to transformation logic that had been thoroughly tested and addressed, which I found particularly valuable. **What do you dislike about dbt?** The learning curve could be smoother, and the user interface would benefit from some enhancements. **What problems is dbt solving and how is that benefiting you?** My priority is to ensure that the strategic decisions I make are grounded in reliable and consistent data. DBT enables this by providing a column that transforms data into clear metrics, eliminating any mistrust in the data. This is achieved without requiring its own visualization, allowing the focus to remain on the quality of the data model. As a result, the agility and speed of reporting are significantly improved. ### 12. Easy-to-Use DBT for Version-Controlled SQL Models **Rating:** 4.0/5.0 stars **Reviewed by:** Dylan C. | RevOps Lead, Enterprise (> 1000 emp.) **Reviewed Date:** May 05, 2026 **What do you like best about dbt?** I use DBT for a lot of our sql models to version control. It's easy to use and helpful **What do you dislike about dbt?** So far there really hasnt been anything wrong with the platform. You need admin that know what they're doing **What problems is dbt solving and how is that benefiting you?** Data model version control and merging updates into snowflake tables on schedules ### 13. Simplifying Data Transformations **Rating:** 4.0/5.0 stars **Reviewed by:** Praveen K. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 01, 2026 **What do you like best about dbt?** Easy SQL-based data transformations and testing. **What do you dislike about dbt?** Large projects can become difficult to manage. **What problems is dbt solving and how is that benefiting you?** DBT automates data transformations, testing, and documentation, improving data quality and pipeline reliability, and development efficiency. ### 14. We finally brought order to complex metric definitions **Rating:** 4.0/5.0 stars **Reviewed by:** Daniele B. | Data Health Engineer, Management Consulting, Small-Business (50 or fewer emp.) **Reviewed Date:** September 05, 2025 **What do you like best about dbt?** It is very nice that dbt gives us the capability to write out our transformation logic as application code. The process of integrating it with Git implies that our whole team may contribute to data models and track changes without hassles, and revert changes as well. Even the separation of the development and production environment out of the box is a tremendous advantage, so we can ensure that we are testing new things without necessarily influencing live reports. Lastly, the automated documentation generation process has made the data models so simple to comprehend, even to the business users, without ever having the touch a SQL. **What do you dislike about dbt?** The initial set up of dbt can be a little fiddly at times and with a mix of operating systems and local database connections. It also lacks its own scheduler, so still we will require an external orchestration tool to carry out our data pipelines. The more advanced Jinja templating and macros proved to be more cumbersome to our team to learn than the simpler SQL. **What problems is dbt solving and how is that benefiting you?** Our greatest weakness prior to dbt was inconsistent reporting amongst departments, this contributed to lack of numbers and big debates on the correct numbers between departments. Marketing could report a figure of new customer acquisition and sales could report an entirely different figure and that could slow down decision making. I we have one version controlled definition of all of our critical business metrics since dbt is in place. Such change came to mean that our leadership team trusts the figures implicitly and no longer spends so much time on reconciliation of numbers, but can actually analyze them. ### 15. DBT at my point of view **Rating:** 4.0/5.0 stars **Reviewed by:** Anandhakumar R. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 28, 2025 **What do you like best about dbt?** 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 **What do you dislike about dbt?** 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 **What problems is dbt 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 ### 16. ELT made easy with just SQL **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Publishing | Mid-Market (51-1000 emp.) **Reviewed Date:** June 18, 2025 **What do you like best about dbt?** 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. **What do you dislike about dbt?** Sometimes the error is not described aptly. This makes parsing error and debugging difficult. **What problems is dbt 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 ### 17. A game changer for dashboarding **Rating:** 4.0/5.0 stars **Reviewed by:** Servio Q. | Software Engineer, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** October 30, 2024 **What do you like best about dbt?** 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 dbt?** 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 dbt 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 ### 18. DBT(Data Build Tool) to build Excellent data models for Quickly and collaboratively **Rating:** 4.0/5.0 stars **Reviewed by:** MAMIDALA V. | Senior System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** November 19, 2024 **What do you like best about dbt?** 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. **What do you dislike about dbt?** 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 dbt 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. ### 19. 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 ### 20. 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 ### 21. 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. ### 22. 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. ### 23. 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) ### 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. 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 ### 26. Great tool to get more visibility into data warehouses **Rating:** 4.0/5.0 stars **Reviewed by:** Rui M. | Data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** Being able to analyse dependencies between data models easily by following the lineage graph. Also, being able to embed tests while creating data models in a straightforward and fast way reduces the tendency to look at testing as an afterthought, effectively making data pipelines more robust. **What do you dislike about dbt?** It is still not possible to precisely pinpoint the root cause of a certain error. dbt is able to identify the table where the error happens, but not the exact fields involved in it. **What problems is dbt solving and how is that benefiting you?** I used to spend a lot of time trying to figure out the dependencies between data models. With dbt I just have to check the documentations, specifically the lineage graph, and I know in an instant how multiple different data models are related. ### 27. Good product to transform raw data and pipeline it to analytics and business needs **Rating:** 4.0/5.0 stars **Reviewed by:** Alfredo L. | Enterprise (> 1000 emp.) **Reviewed Date:** February 28, 2023 **What do you like best about dbt?** What I use the most is the documentation feature. It is very robust and complete, which helps me understand where the features I use daily come from and how they were built. **What do you dislike about dbt?** I'd say there is a learning curve to start using it which could be smoother. Some basic guidelines on the basics would help a lot. **What problems is dbt solving and how is that benefiting you?** Understand how features from the tables are built ### 28. dbt infrastructure has helped us build a data warehouse with a firm foundation **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** May 11, 2023 **What do you like best about dbt?** I love it's self sustainability and the ease of implementation and documentation **What do you dislike about dbt?** upgrading dbt versions is sometimes a hassle **What problems is dbt solving and how is that benefiting you?** dbt is making it possible to very specifically organize our data and make it very easily accessible ### 29. Overall good developer experience and great ELT solution **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Insurance | Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** - Git integration and software engineering best practices - Lineage - Metric layer - Tests - Incremental materialisations - Quite quick response times for cloud support tickets **What do you dislike about dbt?** - Lack of being able to run changes on a dev environment without having to create a separate project - Lack of explanation of best practices for how developer and deployment schemas should be set up/named **What problems is dbt solving and how is that benefiting you?** - We needed a more scalable solution to the python scripts we were running to perform ELT on our data - Batch processing for redshift data which we then use in our prod systsem ### 30. dbt review **Rating:** 4.0/5.0 stars **Reviewed by:** David S. | Principal Architect, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** Highly functional SQL transformational tool. Simple to start, but with adequate levels of complexity available to add if necessary. Good documentation. **What do you dislike about dbt?** Nothing comes to mind as the product provides a great solution **What problems is dbt solving and how is that benefiting you?** Internal data transformation in a cloud warehouse. Very few other products accomplish this as well. ### 31. Newbie to dbt **Rating:** 4.0/5.0 stars **Reviewed by:** Scott G. | BI Team Lead, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** Easy to set up SQL based UI is intuitive **What do you dislike about dbt?** Lack of logs/metadata on job runs, the area around that isn't strong **What problems is dbt solving and how is that benefiting you?** We are able to model our data for Looker outside of looker, so no need for PDTs etc ### 32. Good if you have the software development experience and desire to manage database models as code **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Real Estate | Mid-Market (51-1000 emp.) **Reviewed Date:** June 14, 2022 **What do you like best about dbt?** 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 dbt?** 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 dbt 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. ### 33. Very powerful tool **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Mid-Market (51-1000 emp.) **Reviewed Date:** March 09, 2022 **What do you like best about dbt?** DBT is critical to my organization and so far the tool has been very simple to use. My favorite feature is the interactive flowchart! absolutely game changing **What do you dislike about dbt?** I think editing in DBT could get a little confusing with the different steps that are needed to update the code. **What problems is dbt solving and how is that benefiting you?** We use DBT to clean and transform our data before it is synced into our BI tool ## 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?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-13+03%3A16%3A32+-0500&secure%5Bsession_id%5D=570867e8-bbe8-4d97-8ec6-a883f77b211a&secure%5Btoken%5D=824911fbe642aa250fc0ecc3e8bebf0fb4ecb49683b949c70ac2a47c4d597bad&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 - Customizable Reports - Marketing Reports - Sales Reports - Activity Dashboard - Interactive Reports - Customizable Reports - Customizable Reports - Activity Dashboard - Customizable Dashboard **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 - Reporting/Analytics - Predictive Analytics - Visual Analytics **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 - Non-Relational Transformations - Data Extraction **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 **Additional Functionality** - Data Mapping - Monitoring - Charting - Integration Management - Reporting/Analytics - Ad hoc Analysis - Access Controls/Permissions - API - Match & Merge - Real-Time Monitoring - Metadata Management - Pipeline Management - Job Scheduling - Dashboard Creation - Data Storage Management - Multiple Data Sources - Data Import/Export - Generative AI - Data Quality Control - Data Connectors - Customizable Reports - Single Sign On - Version Control - Visual Analytics - Accounting Integration - Real-Time Data - eCommerce Management - AI Copilot - CRM - Data Visualization - SSL Security - Search/Filter - Real-Time Analytics - Data Capture and Transfer - Collaboration Tools - Performance Management - Data Synchronization - Drag & Drop - Data Replication - Activity Dashboard - Database Support - Workflow Management - Alerts/Notifications - Predictive Analytics - Data Migration - Third-Party Integrations - Reporting & Statistics - Data Analysis Tools **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 - Real-Time Data - Data Capture and Transfer - Trend Analysis - What-if Analysis - Statistical Analysis - Data Blending - Ad hoc Analysis - Third-Party Integrations **Functionality** - Identification - Correction - Normalization - Preventative Cleaning - Data Matching - Real-Time Data **Cloud Deployment** - Hybrid cloud support - Cloud migration capabilities **Generative AI** - AI Text Generation - Generative AI **Agentic AI - Data Warehouse Automation** - Proactive Assistance **Performance Optimization - Semantic Layer Tools** - Query Caching & Acceleration - Adaptive Query Optimization **Additional Functionality** - Data Analysis Tools - AI/Machine Learning - Data Extraction - Reporting/Analytics - AI Copilot - Data Mapping - ETL - Big Data Analytics - Data Quality Control **Additional Functionality** - Parallel Processing - Ad hoc Analysis - Multiple Data Sources - API - In-Database Processing - Monitoring - Real-Time Reporting - Data Synchronization - Real-Time Monitoring - Data Connectors - Performance Metrics - Ad hoc Reporting - Alerts/Notifications - Access Controls/Permissions - Drag & Drop - Data Visualization - Data Import/Export - Match & Merge - Data Transformation - Secure Data Storage - Data Extraction - AI Copilot - Customizable Reports - Activity Dashboard - Data Migration - In-Memory Processing - Data Mapping **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling - Natural Language Search - Visual Discovery - Data Blending - Data Blending **Operations** - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks - Data Discovery **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 **Additional Functionality** - Data Warehousing - Drag & Drop - Activity Dashboard - Data Connectors - Ad hoc Reporting - Customizable Reports - Alerts/Escalation - Templates - Forecasting - Data Migration - Data Transformation - Access Controls/Permissions - API - Data Cleansing - Data Synchronization - AI Copilot - Dashboard Creation - Data Extraction - Data Security - SSL Security - Collaboration Tools - No-Code - High Volume Processing - Database Support - Search/Filter - Generative AI **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services - Real-Time Analytics - Reporting/Analytics - Real-Time Analytics - Reporting/Analytics - Visual Analytics **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Advanced Intelligence - Semantic Layer Tools** - Natural Language Query Interface - Semantic Layer for AI/ML Models - Recommendation Engine **Additional Functionality** - Metadata Management - Collaboration Tools - Search/Filter - Workflow Management - AI Copilot - Third-Party Integrations - Data Synchronization - Data Import/Export - Customizable Rules - Master Data Management - Monitoring - Data Transformation - Multiple Data Sources - Self Service Portal - Customer Database - Data Verification - Data Migration - Multi-Language - Single Sign On - Duplicate Detection - Email Address Extraction - Reporting/Analytics - Data Profiling - Data Extraction - Data Mapping - Address Validation - Match & Merge - Performance Metrics - Visual Analytics - Version Control - API - Data Capture and Transfer - Access Controls/Permissions - Compliance Management - Data Discovery **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 - Real-Time Data - Real-Time Data - Third-Party Integrations - Third-Party Integrations **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications - Mobile Access - Metadata Management **Additional Functionality** - Customizable Branding - Natural Language Processing - Data Extraction - AI Copilot - Ad hoc Reporting - Real-Time Reporting - Publishing/Sharing - Collaboration Tools - Strategic Planning - Self Service Data Preparation - Trend Analysis - Text Analysis - Real-Time Monitoring - Data Synchronization - Widgets - Benchmarking - Performance Metrics - Data Mapping - Generative AI - Trend/Problem Indicators - Customizable Templates - Access Controls/Permissions - Data Import/Export - Profitability Analysis - OLAP - Alerts/Notifications - Search/Filter - Drag & Drop - Data Connectors - Multiple Data Sources - Key Performance Indicators - Dashboard Creation - Role-Based Permissions - Data Mining - Forecasting - Ad hoc Query ## Top dbt Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (1,335 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (860 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,145 reviews)