SqlDBM Reviews & Product Details

I like that modelers in my company can work together on the same project in parallel. In addition, the recipients and users of the data models we create can view them easily, which helps them answer their business questions much more efficiently. It’s also great for documenting data models - no more Visio-based drawings! Customer support is excellent too - cherry on the top! Review collected by and hosted on G2.com.

One area that can definitely be improved is CI/CD. Everything around releasing and deploying could be handled much better, so we wouldn’t have to implement our own custom scripts to manage changes and then rely on additional external tools to deploy everything. Review collected by and hosted on G2.com.

SQLDBM excels as an easy-to-use tool that covers (nearly) everything you’d want to do in the data modeling space. It supports the full range of work, from physical code generation to conceptual and logical data models that can help govern an entire org. Review collected by and hosted on G2.com.

Automation and integration options are limited. For example, the APIs feel lacking. SQLDBM is part of the collaboration stack we use as our platform, but integrating it with the rest of our collaboration tools is challenging, and in some cases seems impossible. I don’t want to send stakeholders to SQLDBM, Airtable, Confluence, and other separate tools. Instead, I want to integrate what each of these tools does well into a single platform, including enabling our AI agents to interact with the data models. Review collected by and hosted on G2.com.

As a data architect and data modeler who has worked across enterprise-scale data platforms, cloud migrations, and complex analytics ecosystems, I can confidently say that SqlDBM is one of the most thoughtfully designed data modeling tools available today.

What immediately sets SqlDBM apart is its true cloud-native architecture. Unlike legacy modeling tools that feel retrofitted for modern workflows, SqlDBM was clearly built for today’s collaborative, distributed, cloud-first data teams. The browser-based interface eliminates friction around installation and version control, allowing architects, engineers, and analysts to collaborate in real time with clarity and precision. Using of different colors for different types of objects like hubs/sats/links, in the data vault and also the dimensions/facts in the star schema really make it very intuitive for consumers of the data model.

From a modeling perspective, SqlDBM strikes an exceptional balance between usability and depth. It supports robust logical and physical modeling while remaining intuitive and efficient. The forward-engineering capabilities are reliable and production-ready, and the reverse-engineering functionality significantly accelerates documentation and modernization initiatives. With Snowflake as our data platform, it is a marriage made in heaven.

One of the most valuable aspects of SqlDBM is its approach to governance and collaboration. Versioning, change tracking, and team-based workflows are built into the core experience — not bolted on as afterthoughts. This makes it a powerful enabler for organizations that take data architecture discipline seriously but still need to move fast.

Performance, stability, and scalability have been consistently strong in my experience, even with large and complex models. The platform handles enterprise-grade schemas with ease while maintaining responsiveness and clarity in diagramming.

In an era where data architecture must support agility, automation, and cloud-native scale, SqlDBM delivers exactly what modern data teams need. It reduces friction, increases transparency, and elevates the overall modeling practice within an organization. Review collected by and hosted on G2.com.

selecting specific objects for database documentation is in progress, so not a usable feature at this time. We have to import documentation for all the tables in a data model than specific objects. Review collected by and hosted on G2.com.

SqlDBM becomes straightforward to use once you get accustomed to it, and it has addressed what used to be our biggest challenge: data modeling with business before development. When our team was searching for a solution to this issue, we discovered that SqlDBM was the only tool on the market that truly fit our needs. The product team is approachable and responds quickly to requests for changes or bug fixes, making the overall experience even better.

We are using SqlDBM every day, and this greatly increase our speed of delivery. Review collected by and hosted on G2.com.

Its sometimes slow when you have alot of data and many layers in your dataplatform.

However, they have now implemented a solution for this

Its quite expensive for the few amount of modellers you get, but you can switch those around.

The tool is lacking some features, but most of them are in the roadmap. Review collected by and hosted on G2.com.

I appreciate how SqlDBM significantly aids in our data modeling processes, allowing us to work across vastly different datasets with ease. The platform is very good, and my team finds it quite easy to use, which enhances their efficiency. Additionally, the customer service and support provided by SqlDBM have been fantastic, addressing any issues promptly and effectively. This level of support and ease of use gives me confidence in the platform’s ability to solve most of our problems. Although no specific feature stands out as the most used, the overall experience and flexibility of SqlDBM suit the diverse ways in which my team utilizes the tool. Review collected by and hosted on G2.com.

I think a better understanding of the roadmap and what new things are coming on board would be very helpful. We would like to understand the future of what SqlDBM is going to bring to customers over the next five to ten years. Review collected by and hosted on G2.com.

I really like the ease of use that SqlDBM offers, making it simple to share models and collaborate. Their modern cloud-first approach resonates with our needs. The UI is thoughtfully designed, and their strong documentation alongside good training guides really help in understanding the platform better. Review collected by and hosted on G2.com.

I would like better dates and information on their upcoming releases. Some end-to-end worked examples using data vault and dimensional models would also be nice. Review collected by and hosted on G2.com.

SqlDBM is the best Cloud-based data modeling tool that exists on the market today. They also do a great job of continually looking to improve their tool by incorporating user feedback as well as looking for integration partners like databases (in our case Snowflake), Git, and even software tools (e.g. Salesforce). Forward engineering YAML files to generate our dbt files works well and reverse engineering databases to ensure the SqlDBM model stays in sync with our database environments works very well. Their product support team is extremely responsive, and many times I've had daily turn-around to address our issues. Finally, the product is very easy to use and provides the ability to create subject areas and diagrams that make sense for our developers and analytical teams to view the models. And the dictionary export feature, makes it very easy for our data stewards to update business definitions in excel and reimport them back into the SqlDBM. Review collected by and hosted on G2.com.

Most of mine are nits and I'm sure may be addressed in future releases; however, they are not preventing me from effectively building our data models today. For example, the ability to create straight line relationships. The ability to color relationship lines. The ability to bold or color column/field names. This would make data model presentations run smoother to show changes (i.e. color, bolded items) and make dimensional layouts look prettier. Review collected by and hosted on G2.com.

Fairly intuitive, easy to reverse engineer and build useful diagrams for sharing with end users of the data. Can check out models so nobody overwrites changes. Ability to create yml files for dbt is very nice. Review collected by and hosted on G2.com.

We have not had a high adoption rate for modeling in SqlDBM first since Snowflake and dbt are our general starting points. We've used it for reverse engineering mostly. This is not a knock on SqlDBM but rather a process that doesn't yet require one of the main uses of the tool. Review collected by and hosted on G2.com.

We like that SQLDBM makes data modeling feel approachable without losing depth. Most tools we’ve seen in the past were either too academic or too clunky. With SQLDBM, our teams can quickly turn ideas into diagrams the business can work with, while still having the governance and structure needed at enterprise scale. We’re also encouraged by where the product is headed with AI — copilots that can document or even suggest better structures feel like the future of this space. Review collected by and hosted on G2.com.

Honestly, not much. If anything, we’d like to see more integrations available out-of-the-box. That said, the pace of iteration is impressive, and the API fills many of the gaps today. Review collected by and hosted on G2.com.

Super easy to start using and get immediate value, doesn't require extensive setup, config, infra, or other overhead Review collected by and hosted on G2.com.

Improvements to core functionality are extremely slow compared to rate at which bells and whistles are released Review collected by and hosted on G2.com.