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.

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.

Feature Requests delivered at lightning speed by one of the product support staffs I have worked with. The training is top notch and free via their Data Modeling Academy or via personal sessions with their Customer Experience Mangers and Support Staff, no more burning through contractual support minutes. They are there when you need them. The cloud-based model management is a huge plus compared to other tools that require you to spin-up a database to hold your data models off of your local drive. You get access to the tool on the cloud, set up a few controls like admins, and you are ready to model.

With SqlDBM, you won't spend a week commissioning servers, installing the tool and repository, writing custom macros and making the tool brittle like its competitors after doing things like automatic conversions, templates (naming or repeated fields), and other data modeling standards enforcements right "out of the box." What makes SqlDBM the best is a great product with monthly, seamless, cloud-based version releases; it's collaboration with Snowflake; its simplicity; and its incredible staff. Review collected by and hosted on G2.com.

SqlDBM is a newer data modeling tool born from physical data modeling stock, but they have done a tremendous job creating a logical modeling product; and with monthly releases, they will be perfect in no time. By the time my criticisms are published, they may not be valid anymore. I would like to see seamless integration between modeling layers where they are treated like separate files so that conversions like denormalizations and natural key to surrogate key mappings are preserved from CDM to LDM to PDM and back. SqlDBM is like 90% there already. Other tools were just as clunky as a remember. I'd like to complain more, but when I have an issue, I submit a feature request or open a support ticket, and they are on it immediately with a satisfactory conclusion in a couple days. None of the major competitors do this. Learning the tool can be tough, but they set you up to success, if you fail at it, you aren't trying. Ever try to hop right into the latest erwin release after a couple years away? The help is many releases old and hard to find online. Review collected by and hosted on G2.com.

SqlDBM is a SAAS tool, the only one available for the Google BigQuery platform. It's easily accessible, quite intuitive in navigation, offers collaborative work through branching, provides versioning, which allows to step back and compare versions. Diagrams can be saved into a visual document; the model can be exported into Excel document to populate descriptive information and load it back into the model. Governance features allow to create labels on column and table level. After a year of use, we are still discovering and learning, as there is a wealth of functionality.

Getting started with SqlDBM was easy with the support staff that is both knowledgeable and responsive. The vendor is flexible and accommodating, aiming at your success with the tool. There is abundance of easily findable documentation - written and video recordings. We started with reverse-engineering of our datasets into a comprehensive model, and from that point, the tool is being used daily by multiple development teams to design new tables, get them reviewed and approved by both business and IT. Review collected by and hosted on G2.com.

The tool is pricy. It may be challenging to justify the cost.

Some BigQuery features are still not fully supported (struct arrays), but with frequent releases, we expect it to be resolved soon. Review collected by and hosted on G2.com.

Its a very light, easy to learn and easy to use tool. Its an elegant low cost modelling solution that works for solution and organization of all scales. SQLDBM support is simply awesome, in terms of timeliness and responsiveness. SQLDBM get easily integrated with GIT, DBT and any tool that can ingest REST API output. Review collected by and hosted on G2.com.

We should have feature to add conceptual model in sqlbdm. Review collected by and hosted on G2.com.

This software makes it easy to go from idea to structured, governed data product (without the chaos of legacy tools). It’s cloud-native, clean, understands SQL syntax and integrates with everything. Cross-functional collaboration is perfect: data engineers, analysts, and business users can all work together on the same platform (with shared visibility into how data is structured and why). Review collected by and hosted on G2.com.

No major issues. More layout options when exporting diagrams would be nice for executive presentations, but that’s more of a nice-to-have than a need. Review collected by and hosted on G2.com.

SqlDBM is a great tool. The best one of data modelers for Snowflake on the market. I think they found a way to make the tedious work of modeling databases easy, without sacrificing on the functionality. That is a golden ratio in software. The interface is user-friendly, collaboration with 3rd party contractors is seamless, and the fact that this is a cloud software is a huge plus. I always recommend them Review collected by and hosted on G2.com.

Nothing to dislike really, it's a great product Review collected by and hosted on G2.com.