--- 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 is a great tool, I wouldn't want to be without it **Rating:** 4.5/5.0 stars **Reviewed by:** Ben T. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** November 02, 2022 **What do you like best about dbt?** Most helpful is how dbt sorts out dependencies for you. Using references in your models, you can tell immediately if a column name change has caused a problem downstream. The DAG graph is fantastic, particularly in the dbtCloud IDE as it updates immediately. Adding basic tests is easy, leading to increased levels of confidence. I know I can run and rerun things without causing problems. If tests pass we're good to go. Freshness tests help make sure that nothing is run if upstream data is not present. This has helped us considerably recently. And exposures, linking to external reports that use the data, is really useful. **What do you dislike about dbt?** Creating a job in the dbtCloud interface and having it default to an hourly schedule. We've only had one minor mishap, but that could be costly with BigQuery. Unless I've missed a setting, that should be off by default. I don't use the Web IDE. Personal preference, I don't want to switch editors. But the lineage graph is awesome, and seeing the compiled alongside the editor is a great feature. **What problems is dbt solving and how is that benefiting you?** Getting data under test so that we know the data makes sense, not just that it has been loaded. The freshness tests have increased confidence that reports are ready to send from our BI tool. We have a history of many similar queries doing the same work. We're using dbt to find and eliminate that duplicated work. ### 2. Awesome product + word of mouth **Rating:** 5.0/5.0 stars **Reviewed by:** Xavier S. | Product Manager, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** November 02, 2022 **What do you like best about dbt?** DBT solves the most fundamental and pressing problems that a small scale, agile data engineering team face. In particular it gives you the ability to take control of your datawarehouse, you decide, manage, develop, test, deploy the end to end steps of the warehouse, regardless of the technology you use. **What do you dislike about dbt?** How it scales with complexity, size and maturity of the company. I struggle to see how this will progress into enterprise level solutions, but I could be surprised ! **What problems is dbt solving and how is that benefiting you?** A variety of technical problems: e.g. how to structure, how to run, how to deploy the logic underpinning the datawarehouse. Some team problems: e.g. how do I ensure that various members of the data engineering team collaborate, share, build together The benefits are clear, with 1 or 2 senior engineers that know dbt, you can build a data warehouse from scratch within a few months, with a budget 10 times smaller than what was possible previously. This is clearly a technological rupture, there is a before and after dbt in the world of data warehouses (for startups ) ### 3. Changed the game **Rating:** 5.0/5.0 stars **Reviewed by:** Sam E. | Head of Analytics & BI, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** Extremely user-friendly, DBT allows our analysts to build, test, document and deploy datasets independently without multiple dependencies on engineering departments. It does not require significant upskilling for junior members and eases knowledge share and confidence through lineage and documentation. **What do you dislike about dbt?** Not much at all! The constant improvements to dbt-core and dbt-cloud keep pace with community requests. Being able to post run results to multiple slack channels would be favorable, but this is in the planned release. **What problems is dbt solving and how is that benefiting you?** Understanding data lineage was a previous problem. Knowing the impact of changes made on downstream datasets was challenging and required significant investigation time. This resulted in slower development and reduced confidence. DBT has allowed the team to onboard new members quicker and with greater confidence leveraging documentation of datasets and lineage. ### 4. Not sure we'd manage without it **Rating:** 5.0/5.0 stars **Reviewed by:** Tim d. | Analytics Engeineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt offers a graceful path for analysts and data practitioners to start leveraging long-standing Software Engineering best practices. Git, ci/cd, and the command line can seem daunting but dbt makes it easy to get started with the cloud IDE, then graduate to the command line/local IDE. The end-result is data resources that are re-usable, composable, tested, and higher quality since they benefit from git-style collaboration. **What do you dislike about dbt?** Limited to transformations in the warehouse and need to rely on separate tool for jobs upstream of the warehouse and downstream delivery. Also, despite the simplicity, some entrenched analysts hesitate to adopt dbt since it's a significant paradigm shift. **What problems is dbt solving and how is that benefiting you?** producing high-quality data resources for stakeholders with diverse needs generating documentation that allow stakeholders to self-serve a system for collaboration on data work ### 5. DBT is a great out-of-the-box solution to huge problems found on data-driven organizations **Rating:** 4.5/5.0 stars **Reviewed by:** Giovani M. | Product Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** I like how it enables analytics engineering (building pipelines) with best practices and has other really useful features (such as documentation and testing). I haven't found a product this complete in other competitors. **What do you dislike about dbt?** I dislike the multiple indentation errors I get on YML, I dislike having to deal with separate "packages" for basic stuff that should be included on DBT regular release, I dislike the "feel" of the typing on DBT Cloud. I feel I can't type code with the same speed and flow I have when using VSCode. **What problems is dbt solving and how is that benefiting you?** DBT is solving SQL standardization, lack of documentation, lack of testing, lack of a good optimized code across companies, which makes us lose less time debugging stuff or trying to figure out someone elses scripts and upstream/downstream tables. ### 6. Amazing User Experience **Rating:** 5.0/5.0 stars **Reviewed by:** Sebhat Y. | Product Analyst, Growth, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** Some of the best things about DBT include its ability to automate and streamline many typical data analysis tasks, its support for a wide range of data sources and destinations, and its intuitive, easy-to-use command line interface. **What do you dislike about dbt?** One thing that was initially hard about DBT is that it can be hard to set up and configure, especially for users like myself who are new to data analytics and using command line tools **What problems is dbt solving and how is that benefiting you?** DBT has benefitted me by allowing me to develop and manage my own data analysis pipelines more efficiently and effectively. By automating many typical data analysis tasks and providing a simple, intuitive interface for working with data, DBT can help me save time and effort when working with large or complex datasets. ### 7. An Absolute Powerhouse **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 03, 2023 **What do you like best about dbt?** There's a lot to like! Especially the ability to: connect dbt with GitHub for version control and documentation, add testing, work on multiple branches at one time, and visualize and manage the relationships between models. We have created documentation that is pulled from the schema files to our BI tool, which is super helpful. Being able to install packages and utilize macros is incredibly powerful as well. I'm also excited about the recent addition of Python - we plan to use it this year. dbt is also surprisingly easy to use; I started using it in my first data job and loved it immediately! **What do you dislike about dbt?** Honestly, there's nothing that I dislike. Jinja has been the most challenging part since it requires thinking differently, but that's just a learning curve and nothing against dbt itself. **What problems is dbt solving and how is that benefiting you?** My use case has been breaking down data silos and building data models that generate a combined view. With dbt, we've automated reports that saved teams a ton of time and gave them a unified view of metrics they've never had before! We've also been able to set up customized tests that alert us to problems within the business/our own software. ### 8. 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. ### 9. Best tool to handle the T of ETL **Rating:** 5.0/5.0 stars **Reviewed by:** Sylvain G. | Lead Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** December 14, 2022 **What do you like best about dbt?** I've been using "traditional" graphical ETL tools for 15+ years (Informatica PowerCenter, Talend, BODS...) and they never seemed "right". More often than not, we just ended up having to use SQL instead of the transformations of the ETL tool, as this was much more robust / performant / flexible. With dbt, the tool finally felt right: - No more useless graphical interfaces. - Heavily focused on leveraging the database performance thanks to SQL. - But still being way better than just SQL since dbt automates everything that can be automated: * No need to create the tables, no need to specify the data types of each column: this all comes automatically from the source. * No need to specify the order of the transformations: this is automated based on the dependencies of each model. * Easy integration of data tests. * Possible to use the Jinja templating language to * Now possible to use python to transform the data. * Good integration of the documentation. * Possible to set up the dbt repository in git to have great version control. * Possible to use dbt cloud with github to automate basic testing of each pull request. * Easy deployment to production thanks to CI / CD / github integration. * Packages available that can answer specific needs. * Great active community behind the tool. * And probably other things ! **What do you dislike about dbt?** The python support opens the door to a lot of possibilities, but it is still new and (at least to me) it is not super clear if we can/should use it to handle some of the "EL" part of ETL (e.g., talk with external APIs to download extra data, or push data to other services). I'm guessing this could work but it is not recommended, at least at the moment. **What problems is dbt solving and how is that benefiting you?** We do all our data warehouse transformations with dbt. The tool makes this simple and robust. dbt helps us automate what can be automated in the development and deployment process, so we can better focus on our specific domain knowledge. ### 10. dbt makes warehousing easy **Rating:** 5.0/5.0 stars **Reviewed by:** Daniel C. | Data Analytics Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** dbt has helped us democratize business logic as a data team and implement it as code in our data warehouse. The ability to manage the scheduling of our cleansed data assets has been a game changer. Having an open-source version that companies can self-host or a paid cloud version creates a low barrier to entry for all companies just getting started or veterans alike. **What do you dislike about dbt?** As with any software, there is a learning curve that they solve with readily accessible learning and a vibrant community on slack. dbt is also moving quickly in its development lifecycle, which seems to introduce bugs. The team is open to feedback and hops in at a moment's notice to help fix any issues. **What problems is dbt solving and how is that benefiting you?** dbt allows our company a low barrier to ELT in our data warehouse, handling scheduling, business logic, and version control of our transformations. This enables contributions across the org to our transformations. ### 11. dbt has allowed our small team to deliver outsized value **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Health, Wellness and Fitness | Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** dbt has provided a framework for implementing a data pipeline that would have required 3x the resources previously. The integrations with Fivetran and Hightouch give us control and insight over the breadth of our data lifecycle that wasn't previously possible. Additionally, the integration with GitHub and built-in testing has allowed us a level of rigor that has dramatically increased the business' confidence in our data output. **What do you dislike about dbt?** We primarily use dbt cloud, and the interface has sometimes been slow and a bit 'clunky' - although the latest release shows promise in resolving some of those concerns! Additionally, it would be great in the future for some tools that help migrate existing SQL native pipelines into dbt. **What problems is dbt solving and how is that benefiting you?** Before implementing dbt, we had transformation/logic living all across the organization (some in native source data systems, some in the Data Warehouse, in our reporting layers, etc.), with little to no oversight. dbt has allowed us to centralize and monitor all of that logic in one tool and provide validation via testing and code review via GitHub. The integrations between other tools in our stack (Fivetrand and Hightouch specifically) have saved us countless hours on modeling and development we would have had to do ourselves and allows us to focus on the 'last mile' and delivering value to stakeholders. ### 12. DBT Cloud is dreadful, do not use. **Rating:** 0.0/5.0 stars **Reviewed by:** Verified User in Computer & Network Security | Small-Business (50 or fewer emp.) **Reviewed Date:** June 19, 2023 **What do you like best about dbt?** Open source DBT is a fantastic tool that makes building robust processing jobs utilising best practice straightforward. **What do you dislike about dbt?** DBT cloud is not ready for production, do not use it. All of our scheduled jobs had been running fine for months, DBT released a change within their infrastructure which meant these jobs could no longer connect to our warehouse due to a missing sasl library. This took close to a week to resolve (despite the exact issue being highlighted to their support team) which meant a week of downtime. Zero compensation was offered. **What problems is dbt solving and how is that benefiting you?** Building analytical datasets. ### 13. No brainer when working with batch processing **Rating:** 5.0/5.0 stars **Reviewed by:** Diego T. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** It gives you a set of tools to improve data governance and quality. It allows developers to apply many software engineering concepts to create a robust data pipeline. **What do you dislike about dbt?** It can be complicated to implement and maintain for a non-technical person or someone who is not proficient in SQL. One of the main limitations for me was that you couldn't run python, which apparently was recently implemented (I haven't tried it yet). **What problems is dbt solving and how is that benefiting you?** It helps you to create a robust data pipeline that holds the "source of truth" for data being used for analysis. Using dbt you can automate a lot of transformations and tests, work in collaboration with your peers and write robust documentation. ### 14. UI based Version Control and ETL Orchestration **Rating:** 4.5/5.0 stars **Reviewed by:** Marshall B. | Business Intelligence Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** September 19, 2022 **What do you like best about dbt?** DBT Cloud lets users set up transformations and orchestrate code runs from a UI-based IDE in the cloud for users who aren't as familiar with using the command line. By leaving engineers to do the coding rather than spending time digging through documentation, our team could reach functionality faster and with less fuss than expected. The ability to test in a safe environment by default before you push your changes to live makes version control easy for users not familiar with git principles. **What do you dislike about dbt?** The cloud-based IDE has a long-ish startup time (30 seconds or longer) and locks you out of editing while it syncs after you save a file. This leads to a little bit of frustration when making minor edits across multiple files. Some other minor frustrations related to the Cloud IDE come to mind, like how column names aren't sensed while you're typing, leading the user to write out column names that could be easily polled during the lineage population. In addition, the testing documentation was a little confusing, leading to me trying different things to get it to work. In the end, I learned that you have to prefix the name of a test model with "test_" to get the orchestrator to see the model as a test. However, after a couple of speed bumps, most issues I have turn out to be minor and do not impact the product's overall usefulness. **What problems is dbt solving and how is that benefiting you?** DBT Cloud has allowed us to migrate from one ETL partner and re-create our transformation files with version control and replicability in mind first and foremost. Additionally, for users who aren't familiar with command line interfaces, we can spin up new users and share work easily while everyone can push to the same deploy environment. ### 15. Analytics Engineering done right! **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** December 01, 2022 **What do you like best about dbt?** dbt's UI is easy to navigate, easy to code in, and easy to run. Documentation is easily accessed and written; I especially like the automatically generated, interactive data model that you can quickly grab when you want to show a stakeholder your work or when you want to discuss a new solution with a colleague. It resolves many of the pain points of analytics engineering. They are constantly making improvements and implementing new things, but if anything is missing, chances are you can find it in one of the many packages written for dbt. The community is also great, and many resources are provided either there, or in the dbt documentation. **What do you dislike about dbt?** I sometimes wish there were more "standard" tests in dbt (such as max character length, min character length, max value, min value). One can make these themselves in macros (and potentially some packages could help with this?), but it would be a nice-to-have! **What problems is dbt solving and how is that benefiting you?** Data is cleaner, data transformation is simpler, and manual joins are no longer needed. In the end, we've created multiple clean and aggregated tables that can act as a source of truth for analysts. Our data is also better documented. ### 16. dbt is amazing! **Rating:** 5.0/5.0 stars **Reviewed by:** Eda J. | Principal Data Cloud Architect - Head of Partner Industry Solutions, Enterprise (> 1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** dbt is a great tool for creating declarative pipelines to transform data while making automation easy and intuitive. There are so many benefits to choosing dbt, but what I like best about dbt is integrating data quality checks in data pipelines. **What do you dislike about dbt?** As the project gets larger and larger, so do the yml files and other project-level configuration files, which makes it less readable. New dbt Cloud IDE usability features are essential to make this better. (Autocomplete, error checking etc.) **What problems is dbt solving and how is that benefiting you?** dbt makes Git integration and CI/CD easier as we don't need to think about defining our frameworks for these. Also dbt packages are extremely helpful. ### 17. 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 ### 18. dbt makes analytics engineerings great and fun **Rating:** 5.0/5.0 stars **Reviewed by:** Kan O. | Data Product Developer and Technical Coach, Small-Business (50 or fewer emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** I love how it aligns with the analytics engineering practices and it can make our team do better analytics **What do you dislike about dbt?** Since my team is using dbt CLI, I dislike that I have to test my queries on the data warehouse first and then change the code to use the Jinja template. It's like I'm doing the work twice. **What problems is dbt solving and how is that benefiting you?** - It helps my team organize the code better and makes it able to reuse the existing models. - The documentation and lineage graph the dbt generates save us a lot of time. - The tests really make us more confident in data quality. ### 19. dbt Cloud is the perfect tool for our data transformations **Rating:** 5.0/5.0 stars **Reviewed by:** Peter F. | Director, Business Analytics, Small-Business (50 or fewer emp.) **Reviewed Date:** October 12, 2022 **What do you like best about dbt?** We have highly complex SQL transformations. dbt allows us to engineer them properly, writing DRY, modular code and using CI/CD. Jinja in dbt allows us to work with SQL data models as objects. We use Fivetran as the E and L in ELT, and Fivetran has an extensive library of dbt packages to provide transformations for many of our data sources. **What do you dislike about dbt?** dbt Cloud's IDE has been improving, but still doesn't have many of the features coders have come to expect from IDEs. And the orchestration available in dbt Cloud is limited. **What problems is dbt solving and how is that benefiting you?** Without dbt to store and maintain our SQL transformation workflow, we would have a mess of SQL scripts that would be very difficult to manage. Without dbt, we would need to write something that had dbt's functionality. ### 20. Jithendra Komhar DBT **Rating:** 5.0/5.0 stars **Reviewed by:** Jithendra K. | Lead software engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** 1. Perfect way of representing the lineage of modes. 2.Easy navigation, good videos for learning about DBT tech stack 3. Excellent support for solving the issues **What do you dislike about dbt?** 1. It would be great if the trial period could be extended to 15 days instead of 8 days. 2. we need to run the models multiple times because of system errors from the dbt cloud. It would be great if it could be solved. **What problems is dbt solving and how is that benefiting you?** We are dbt partners and working on some POCs like Informatica to DBT models to showcase how dbt can be leveraged. we are partnersof DBT ### 21. Everything we use from dbt is wonderful. **Rating:** 5.0/5.0 stars **Reviewed by:** Vinícius M. | Lead Analytics Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** What we like the most, without a doubt, is the docs (lineage) feature. We were able to understand practically all of our data load flow by looking at this feature. **What do you dislike about dbt?** So far I've enjoyed all the features we've used from dbt. Snapshots and tests are still missing, but they will certainly meet our needs. **What problems is dbt solving and how is that benefiting you?** We had a lot of difficulty getting a complete view of our DW load. Many times forgetting to update some visual documentation that we did manually. However, with the docs (lineage) feature of dbt we no longer have this type of problem. ### 22. dbt metadata works well with Monte Carlo **Rating:** 5.0/5.0 stars **Reviewed by:** Cynthia N. | Mid-Market (51-1000 emp.) **Reviewed Date:** March 21, 2023 **What do you like best about dbt?** It allows me to add metadata upstream that can be read by downstream applications. I only have to change the metadata in one place. **What do you dislike about dbt?** The way we have set up our models, there are many, many different versions of the data through the pipeline. It can be hard to figure out which one is the end user model and therefore needs to have the metadata. **What problems is dbt solving and how is that benefiting you?** allows more of the BI team to be involved with the data pipeline ### 23. Can't live without dbt **Rating:** 5.0/5.0 stars **Reviewed by:** Jeff S. | Principal Consultant, Data Architecture and Analytics, Mid-Market (51-1000 emp.) **Reviewed Date:** August 09, 2022 **What do you like best about dbt?** The best thing about dbt is its Customer Service team. They have the best customer support team I've encountered from any product in any industry. They are ready to support your questions. You get an expert on the first chat. I've never needed to escalate to a higher level of support, 100% questions answered every time. Then there's the obvious product stuff we love: Organized data pipelines, easy to naviage DAG to trace back models to the source, automation, and DevOps best practices built into analytics pipelines. **What do you dislike about dbt?** dbt cloud can be improved in the following ways: - autocomplete! (Like intellisense included with apps like dbeaver) - better way to search through files (search for text within a folder) - multiline edit (like in VS Code with CTRL+ALT+Down) - less simplified git actions (like stage only certain files to commit) **What problems is dbt solving and how is that benefiting you?** Our organization has access to a lot of tools with overlapping capability. dbt's DAG and documentation feature make the learning curve worth it. Just don't forget to document your models! :) ### 24. Easy to use, tailor-made for the the cloud, pairs well with Snowflake. **Rating:** 5.0/5.0 stars **Reviewed by:** Eric L. | A, Small-Business (50 or fewer emp.) **Reviewed Date:** August 08, 2022 **What do you like best about dbt?** dbt is based primarily on SQL, which is very easy to use, and paired with databases like SnowFlake, which includes a broad and sophisticated SQL implementation, there is no end to the transformations you can do. Plus, there is a considerable open source library of code to perform common transformations based on general ETL needs, and transformations specific to many cloud applications. Companies like FiveTran, for example, produce and provide sophisticated dbt packages that make challenging tasks very easy. Finally, the user interface was obviously designed and created by people who have done this work. Once you get familiar with it, repetitive and mundane tasks are done quickly and easily. Error reporting and debugging works smoothly. I am still relatively new to this, but I am really enjoying dbt, and looking forward to being engaged with the community that seems willing and excited to contribute to the growth of the product and development of the user community. dbt transformations use the database engine to provide the resources to do ETL, and **What do you dislike about dbt?** I think the surrogate key module in dbt_utils misses the mark. Maintaining meaningless integer surrogate keys is the preferred approach in my opinion. They use less space, and perform faster. **What problems is dbt solving and how is that benefiting you?** Fast and efficient ETL: easy and fast to develop, fast to execute. Leaves the data in place so there is little latency and minimal egress/ingress charges. Paired with data pipelines like FiveTran, and a data warehouse engine like SnowFlake, the process of getting data from any cloud or on-prem application into a data lake, or data warehouse where it can be sued for reporting, analytics and more is considerably faster than any combination I have used in the past. ### 25. dbt modernizes my pipelines **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** I love how the types of materializations are well documented and presented as a journey toward various stages of dbt maturity - dont start with incrementals. I love how dbt is SQL driven, even when introducing macros. **What do you dislike about dbt?** I can't seem to keep the dbt Cloud and dbt Core documentation separate when I arrive from a google search or forum. I would also love to talk about bringing dbt Cloud Enterprise into the GCP Marketplace to make it easier to recommend to my customers. **What problems is dbt solving and how is that benefiting you?** dbt modernizes my data platform by enabling me to treat my data pipelines and warehouse as code, templates, and DAGs. Without dbt, I have to broaden my toolset to accommodate other non-SQL tools, which can lead to less DRY code. ### 26. dbt has fundamentally changed how I work with data **Rating:** 5.0/5.0 stars **Reviewed by:** Christopher G. | Teamlead Analytics & Performance, Mid-Market (51-1000 emp.) **Reviewed Date:** October 12, 2022 **What do you like best about dbt?** After working with BigQuery in the marketing and digital analytics space for a few years, we embraced dbt about 1,5 years ago. It has completely transformed our thinking about data modeling, quality, accountability of data products and documentation. From an analyst's perspective, dbt brings necessary engineering principles into data work and helps build data products for the longer term. **What do you dislike about dbt?** There are always aspects that can be improved. The ecosystem has seen such fast growth that the space has become fragmented. Many tools built on top of dbt or are tightly integrated could be part of a more extensive suite. **What problems is dbt solving and how is that benefiting you?** Organizing data transformations in BigQuery and building high-quality data marts for business use cases ### 27. DBT the Design Tool for the Data Engineers **Rating:** 5.0/5.0 stars **Reviewed by:** M M K. | Data Engineer , Small-Business (50 or fewer emp.) **Reviewed Date:** April 27, 2023 **What do you like best about dbt?** Ease with which it integrates with Python and Postgres Database. **What do you dislike about dbt?** No native connector for Spark Datawarehouse. There is connector to other warehouses like Snowflake/BigQuery/Redshift **What problems is dbt solving and how is that benefiting you?** Data Modeling and Data handling are the 2 key areas that DBT helps to automate. DBT makes it a breeze to move the data between schema and stages programmatically ### 28. I can define my 6 month experience with dbt with the word Productivity **Rating:** 5.0/5.0 stars **Reviewed by:** Lucas M. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** I believe that what I like most is the possibility of versioning the codes. This greatly facilitates the maintenance and evolution of projects, generating a lot of productivity for the team. **What do you dislike about dbt?** Taking into account the maturity of the analytical engineering area, in 6 months of use we found no disadvantages. **What problems is dbt solving and how is that benefiting you?** One of the main points that dbt is solving is the organization of our DW, data modeling is extremely flexible, easy application of version control, data quality testing, low learning curve and integrated documentation. ### 29. Elegant product which both simplifies & improves the role of a Data Analytics Engineer **Rating:** 5.0/5.0 stars **Reviewed by:** Douglas M. | Contract Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** December 06, 2022 **What do you like best about dbt?** DBT is a well-thought-out product which keeps the focus on SQL but also allows proper software engineering techniques to be applied **What do you dislike about dbt?** IDE is still inferior to VSCode. Jinja is great but also can be very messy to use. Would prefer a cleaner separation which allows pure Python code to be written. **What problems is dbt solving and how is that benefiting you?** Transformation of Business Logic in a Data Warehouse, separation of Development/Test and Production environments with less maintenance than before, allowing the focus to remain on solving business problems. Improved testing and Quality of data. ### 30. Great all around transformation tool **Rating:** 5.0/5.0 stars **Reviewed by:** Leon R. | Data Engineer II, Mid-Market (51-1000 emp.) **Reviewed Date:** July 21, 2022 **What do you like best about dbt?** The model structure and process structure for building complex models in dbt is amazing. Leveraging jinga to compile sql has made complex data problems easier to solve. Integrating with git to add version control to transformations has been a great overall experience that has allowed code deployment processes to take places that normally are skipped. All of this resulting in more reliable transformations with fewer duplicated transformation/business logic. **What do you dislike about dbt?** Dbt overall is a great product with a bright future but as with any software there can be room for improvement. At times the web interface can be unreliable failing to connect to git or unable to commit changes. This can cause valuable work to be lost when working online. The onboarding experience can be difficult when it comes to understanding things like Jinga and how to best leverage dbt and best practices. As the community of users grow i'd expect more content available to reduce this barrier. **What problems is dbt solving and how is that benefiting you?** Making the transformation steps modules and sql based has allowed me to collaborate with many different stakeholders that normally are not comfortable diving deep into code. Jinga has removed the need to do adhawk scripts to generate sql to execute. ### 31. Great software to manage transformations **Rating:** 5.0/5.0 stars **Reviewed by:** Erik J. | Data and Analytics Mentor, Mid-Market (51-1000 emp.) **Reviewed Date:** November 18, 2022 **What do you like best about dbt?** Eady to use, saves the need for a data engineer to manage our transformation pipelines, very scalable for our organization, integrates great with other tools in our tech stack **What do you dislike about dbt?** dbt Cloud UI can be clunky and time consuming to load; without good data governance or guardrail, you can run up high data warehouse costs and a multiplication of tables and views **What problems is dbt solving and how is that benefiting you?** dbt helps us manage all our data transformations in a single location and to schedule jobs that produce all our production tables for analytics purposes (dashboards, reports, models) ### 32. DBT : Instant solution (ELT) - Big Data DE Scenario's **Rating:** 5.0/5.0 stars **Reviewed by:** Ravi K. | Solution Architect, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** The ease with which I have done multiple POC and demonstrated to the customers having their products in various domains. I would say that setup and installation were pretty simple. **What do you dislike about dbt?** I don't see any as of now. Will surely share once I have any. **What problems is dbt solving and how is that benefiting you?** One of the Data Engineering scenarios required an ELT operation, and I found DBT was the best fit for it. The best part is that the computation runs on the core engines. ### 33. 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 ### 34. An amazing product that change the way any company handle data **Rating:** 5.0/5.0 stars **Reviewed by:** Nicolás D. | CTO, Mid-Market (51-1000 emp.) **Reviewed Date:** December 20, 2022 **What do you like best about dbt?** The ability to quickly develop, test and deploy models at scale has increased our team productivity enormously and lead us to focus more on adding value to the company and less on maintaining ETL's **What do you dislike about dbt?** I would love it if the python compatibility became better and faster, it will dramatically change how we build models and I can't wait to see it live. I also think the cloud IDE can be faster **What problems is dbt solving and how is that benefiting you?** The problem of unifying and transforming data to better fit the visualization and analysis needs throughout the different teams in the company. We can now focus on adding value and not in maintaining ETL's ### 35. Easy to use, powerful tool **Rating:** 5.0/5.0 stars **Reviewed by:** Andres R. | Data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** In my company, we embraced dbt cloud only a few months ago, looking for a tool to help us migrate from unserviceable legacy python scripts living on Airflow, which could be replaced with more straightforward SQL model solutions. It has fundamentally changed how the data team works, incorporating software engineering best practices like version control and documentation. It is a solution that not only a data engineer could use or understand. **What do you dislike about dbt?** The Cloud IDE needs some work, and the integration with python should be faster and easier. **What problems is dbt solving and how is that benefiting you?** Separation of test/development environments in the data warehouse, replacement of old and unserviceable processes, management of data transformations and load in one place. ### 36. dbt is transformational (pun intended) **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Automotive | Small-Business (50 or fewer emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** dbt is intuitive to learn and use. The community makes implementing dbt feel like joining some kind of social club where everyone just wants you to succeed which is so rare. The documentation makes it super simple to translate an idea into action. **What do you dislike about dbt?** dbt makes writing code very accessible to people which is a double-edged sword. A lot of people new to dbt take a shoot first, ask questions later approach which leads to a lot of technical debt and cloud computing expense down the road. **What problems is dbt solving and how is that benefiting you?** Cleaning data and translating business logic into version-controlled models to maximize the efficiency of the data team and deliver value faster. ### 37. The best tool for data engineering on Snowflake! **Rating:** 4.5/5.0 stars **Reviewed by:** Erik L. | VP, Data and Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** December 09, 2022 **What do you like best about dbt?** I appreciate the ability to generate a DAG quickly. This capability is beneficial for developers to extend the data warehouse while understanding what may be impacted downstream. The recent improvements to the cloud IDE have been substantial. **What do you dislike about dbt?** The cloud IDE is going through a complete revamp, and during that time, there have been some glitches in how it operates. There have also been a few outages over the past few months, but nothing of major consequence. **What problems is dbt solving and how is that benefiting you?** We use DBT as part of our tech stack for our embedded analytics product. It has allowed us to go from no data warehouse to a stable and agile data warehouse in weeks. ### 38. data scientist **Rating:** 5.0/5.0 stars **Reviewed by:** Yingwen L. | Mid-Market (51-1000 emp.) **Reviewed Date:** March 31, 2023 **What do you like best about dbt?** Easy to set up a test on unique row_id and add descriptions of tables or columns. The "Format" function is super helpful. It makes coding clear to read. **What do you dislike about dbt?** So far, I don't find anything I dislike. just a suggestion that adding --full-refresh on quick bottoms (ex: build, run) **What problems is dbt solving and how is that benefiting you?** testing unique. running time. ### 39. dbt helps us manage and collaborate data transformation very efficiently **Rating:** 5.0/5.0 stars **Reviewed by:** Renno I. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** Easy to maneuver dbt cloud IDE to complete our models, version control for collaboration, jinja templating for python power, dbt tests to ensure accurate result, yml file, a centralized space to provide clear descriptions, and many more... oh of course, dbt docs **What do you dislike about dbt?** Haven't found one yet; maybe some built-in sqlfluff? I know it's already in progress. **What problems is dbt solving and how is that benefiting you?** Keeps track of changes between engineers and documents easily the "why" behind the changes. ### 40. dbt is a gamechanger **Rating:** 5.0/5.0 stars **Reviewed by:** Chris P. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** dbt has transformed the way we work for the better. Not only does it enable modularity and re-usability across our data warehouse, but it also enabled us to easily set up development environments which resulted in much faster iteration time. **What do you dislike about dbt?** The dbt cloud console is confusing and a bit difficult to use. **What problems is dbt solving and how is that benefiting you?** dbt enables faster development of our data warehouse by providing dev tools and documentation out of the box. ### 41. dbt is the single most powerful tool in our arsenal **Rating:** 5.0/5.0 stars **Reviewed by:** Robert C. | Head Of Operations, Mid-Market (51-1000 emp.) **Reviewed Date:** October 12, 2022 **What do you like best about dbt?** dbt allows us to create a federated data model including information from all of our operational platforms. As a result, we've eliminated swivelchair tasks, latency in report reconciliation, and blindspots in our ability to create a 360 degree view of our clients. **What do you dislike about dbt?** I really don't have any complaints. To the extent that anything has been difficult, it's because I'm using something that is inherently a very complex tool. That said, the fact that a layperson without actual engineering experience can build with dbt says a lot about how well it'd built. **What problems is dbt solving and how is that benefiting you?** Like all businesses, we have data in many, many platforms and none of them are capable of reporting comprehensively on our business. dbt allows us to federate the data across those platforms and gives us a single data model to operate from. ### 42. The era of shaky SQL templates is over **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Telecommunications | Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2022 **What do you like best about dbt?** DAG execution when rebuilding an entire schema/mart, docs, tests (referential integrity especially), dbt utils and packages (redshift utils especially) and many more. **What do you dislike about dbt?** There is little that I dislike, IDE version 2 has improved, one can still over-write default macros in order to achieve custom functionality. **What problems is dbt solving and how is that benefiting you?** For instance, my first three months with tool were spent on a migration of all kinds of different sql processes which accumulated over 5 year within the company, now all simplified and unified under one repository. The main problems we solve are staging transformations (used by legacy reporting) and building dimensional schema for self-service analytics as well as embedded analytics. ### 43. dbt is very intuitive to use and works great in our data tool stack **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** December 15, 2022 **What do you like best about dbt?** dbt cloud's structure and the ease of transforming the data without worrying about the warehouse connection. Also being able to see the lineage easily to understand the connections. **What do you dislike about dbt?** sql help could be much more improved and also showing when there is a false syntax before having to compile or run the preview because there are many times that you need to go out of the platform just to check sql syntax **What problems is dbt solving and how is that benefiting you?** transformation of that in a structural way where you have control over the lineage greatly and surfacing reliable models that can be exposed to consumers directly ### 44. dbt for me has revolutionized the workflow around transforming data used for analytics **Rating:** 5.0/5.0 stars **Reviewed by:** Eugene A. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** Dbt creates an entire streamlined workflow around transforming data from a source in a way that is best used for analytics **What do you dislike about dbt?** Even though there is a lot of emphasis put on dbt cloud, the open source core version is still widely used. **What problems is dbt solving and how is that benefiting you?** It is solving the problem of having an established workflow around transforming data for the purpose of analytics ### 45. dbt is a one-stop destination for warehouse-native modelling and transformation **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 13, 2022 **What do you like best about dbt?** 1. Analytics as code 2. Documentation-first experience 3. New capabilities and roadmap look promising (eg. Semantic Layer) 4. dbt Community and conferences are helpful for team to grow **What do you dislike about dbt?** 1. Not much honestly! :) - all of the below is good to have 2. dbt Docs is slow when there are a ton of models 3. Enterprise edition pricing is unclear/not public **What problems is dbt solving and how is that benefiting you?** dbt Labs is helping us model the raw data on our Snowflake instance as code. It helps us keep our team lean and make data available as models/metrics - reusable assets for our data team's consumers. ### 46. DBT is saving our time and money **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 15, 2022 **What do you like best about dbt?** I love that we can document destinations and sources and automatically test the sources. We recently tried making dbt package and hopefully will soon bring it to production. **What do you dislike about dbt?** I miss the option to define loaders the same way we can define exposures. We are using 4 different loaders, and it would be beneficial to document the responsible person and the link to the loader. **What problems is dbt solving and how is that benefiting you?** DBT is solving the automagical orchestration of our queries, testing, documentation, and much more. And it is built on top of git!! At the same time, the dbt community is fantastic. ### 47. Fantastic SQL orchestrator that bridges the gap between analysis and programming **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Games | Small-Business (50 or fewer emp.) **Reviewed Date:** December 09, 2022 **What do you like best about dbt?** * All models, configurations and tests stored as version controlled code * OSS as well as a managed SaaS-service * Easily overviewable lineage & dependency trees **What do you dislike about dbt?** * There are some hidden complexities/nitty-gritty details you need to figure out before dbt becomes a powerful tool * Parts of the documentation lack example(s) or have examples using legacy/old standards **What problems is dbt solving and how is that benefiting you?** * dbt collects and orchestrates all transformations that before were scattered between analyst's own Drives, embedded within tooling or otherwise just laying around. I think this is one of the most powerful things dbt has done for us thus far. ### 48. 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 ### 49. Our time is exclusively dedicated to providing value with this tool as it's reliable and easy to use **Rating:** 5.0/5.0 stars **Reviewed by:** Jacob B. | Head of analytics, Small-Business (50 or fewer emp.) **Reviewed Date:** December 09, 2022 **What do you like best about dbt?** * With inherited lineage, there is clarity in the transformation process. * Doucmentation & tests easy to config * The transformations require only SQL. * Open source first approach **What do you dislike about dbt?** * Visualization of test results & jobs run time is lacking. **What problems is dbt solving and how is that benefiting you?** * ease of use & visibility to the transformation process. * don't waste time on infra ### 50. Resolving sql’s shortcomings with dbt **Rating:** 5.0/5.0 stars **Reviewed by:** Michael F. | Analytics Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 29, 2022 **What do you like best about dbt?** Being able to easily onboard 10+ analysts, has significantly increased our speed to produce data models. This has enabled us to unblock our data teams and make sure they are producing high-value work, which would not have been possible without dbt dbt’s integration with jinja allows the implementation of software engineering practices into the data world, this helps resolve the limitations that exist in vanilla SQL. For example, keeping SQL DRY can be a challenge, with dbt jinja repeated code is easily written once and looped in a loop, or wrapped in a macro. dbt cloud enables an accessible front end for new developers, and automatic updates are a nice feature for administration. The lineage graph enables quick analysis of downstream impacts of changing a model, no more searching the repo for a table and crossed fingers at release time. **What do you dislike about dbt?** dbt cloud’s ide can be slow to open and has limitations that have been acknowledged by dbt. **Recommendations to others considering dbt:** The rapid onboarding was a good way to get our team of 10 developers up to speed quickly. Additionally, we have implemented a policy of developers completing the dbt fundamentals course online before taking branches of our prod repo. The fundamentals videos are a very quick way to get developers who have never seen dbt before thinking in the dbt mindset. **What problems is dbt solving and how is that benefiting you?** Brighte is on a mission to make every home sustainable. Brighte’s data team is supporting this mission by building an integrated data warehouse, supporting data to analysts distributed thought the business. dbt cloud facilitates the enablement of data analysts to contribute to developing the data warehouse, increasing throughput of development, and freeing our centralised analytics engineers to work on complex problems and develop architecture vision. ## 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=3§ion=pricing&secure%5Bexpires_at%5D=2026-07-21+15%3A42%3A59+-0500&secure%5Bsession_id%5D=fdad5724-35d4-4267-ae5f-7025868b0c8b&secure%5Btoken%5D=d3f5c93976c88310da0dce154c0098b55e38665f4571cdba2fda9d923ec2fe94&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 (1,323 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (846 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,144 reviews)