SqlDBM

Data Modeling Software · San Diego, CA

SqlDBM Reviews

SqlDBM is a cloud-native enterprise data modeling platform used by teams at Hulu, Zendesk, Sanofi, PwC, and Baptist Health. It covers conceptual, logical, and physical modeling with reverse and forward engineering, version control, and native integrations for Snowflake, Databricks, Google BigQuery, Azure Synapse, Amazon Redshift, dbt, GitHub, and GitLab. It pairs schema design with a governed semantic layer, a combination competitors typically split across separate tools, so people and AI agents read one definition of the data. Founded in 2017 and headquartered in San Diego, SqlDBM is SOC 2 Type II certified, a Snowflake Premier Partner, a Databricks Validated Data Partner, and a Google Cloud Partner.

5.0 out of 5
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The verdict

What the reviews add up to

SqlDBM holds a 4.6/5 rating on G2 across 18 reviews, 4.5/5 on Gartner Peer Insights, and 4.8/5 on Capterra. Reviewers most consistently praise the intuitive browser-based interface, unusually fast and personal customer support, and the depth of Snowflake, Databricks, and dbt integrations. Enterprise users highlight built-in governance, naming standards enforcement, monthly release velocity, and a direct favorable comparison against erwin for out-of-the-box standards.

Pros

  • Intuitive, browser-based modeling with no installation or infrastructure to manage
  • Native Snowflake, Databricks, BigQuery, and dbt integrations with reliable reverse and forward engineering
  • Highly responsive support, with free training via the Data Modeling Academy
  • Built-in version control, branching, governance, and naming standards for enterprise teams
  • Monthly releases and fast turnaround on customer feature requests
  • Semantic modeling layer that gives people and AI agents one governed definition of the data

Cons

  • Customers haven't mentioned anything negative in these reviews.

Every review

Reviews of SqlDBM

Strong value and practical pricing

Reviewers describe SqlDBM as a practical modeling tool with useful functionality at a reasonable price. These examples provide positive counter-evidence to complaints about cost.

G

GreyHairedDWGuy

Reddit(opens the original review)

Positive assessment of SqlDBM for data warehouses

However, for basic modelling related to a DW, SqlDBM is fine. They are adding features all the time to it. It is not cheap but you get what you pay for. They do sell a couple levels of functionality so you can pay for what you think you need.

Easy to learn and intuitive to use

Reviewers describe SqlDBM as easy to use, quick to learn, and convenient because it is available online. These comments counter concerns about a steep learning curve.

Collaboration, integrations, and production workflows

Reviewers praise collaboration, Snowflake and dbt integration, schema visualization, and forward and reverse engineering. Their comments show that SqlDBM supports practical data-modeling workflows.

Enterprise modeling, governance, and complex data

Reviewers describe efficient modeling of complex organizational data, higher team productivity, stronger standards, and centralized definitions. This counters the idea that SqlDBM is limited to lightweight diagrams.

Responsive support and active product development

Reviewers describe responsive support, rapid feature delivery, frequent releases, and a product team that listens to users. This provides positive counter-evidence to concerns about support or development pace.