SqlDBM

Overview

SqlDBM is a data modelling platform that runs entirely in the browser, with no desktop client to install. It is aimed at teams designing for cloud data platforms, and supports conceptual, logical and physical models in one place. Logical projects are kept database-independent, with subtypes and supertypes, domains and user-managed data type mappings, and are then generated against a chosen platform.

The working pattern is the familiar one: reverse-engineer an existing database by uploading DDL or connecting directly, edit the model on a diagram, then forward-engineer DDL or an alter script. For Snowflake it can also monitor a live database and show where it has drifted from the model. Projects can be imported from Erwin files or a dbt manifest.

It is built around team working rather than single modellers: several people can work at once, with branching and merging, column-level merge, comments, approval workflows and a tiered permission system. Read-only "consumer" seats let business users look without editing. Recent releases add an AI copilot, an MCP server and a semantic layer, alongside global standards that apply naming conventions and templates across every project.

The vendor says the platform handles metadata only, never your data, and lists SOC 2 Type II, audit logs and optional customer-hosted storage. It claims over 400,000 users, and names DocuSign, Pfizer and Zendesk among its customers.

Key features and capabilities

The same headings are used for every data modelling & design entry, so two tools can be read side by side.

Model types

• Conceptual, logical and physical models in one project
• Database-independent logical models with subtypes, supertypes, domains and data type mappings
• Semantic modelling, plus global modelling for organisation-wide reference objects
• Table and column templates, for example a type 1 dimension

Forward and reverse engineering

• Forward engineering to DDL, and alter scripts for changes
• Reverse engineering by DDL upload, or a direct connection for cloud platforms
• Snowflake schema monitoring, comparing the model against the live database
• Imports Erwin projects and dbt manifests

Platform coverage

• Cloud platforms: Snowflake, Databricks, BigQuery, Amazon Redshift, Azure Synapse, Microsoft Fabric
• Transactional databases: PostgreSQL, SQL Server, Oracle, MySQL, AlloyDB, and Teradata in the app
• Direct connections offered for the six cloud platforms

Collaboration and version control

• Several modellers at once, with branching, merging and column-level merge
• Comments, approval workflows and a tiered permission system
• Read-only consumer seats for business users
• Version control of the model itself

Standards, glossary and governance

• Global standards: naming conventions, case rules, glossary and templates across projects
• Custom metadata fields, for example owners, source-to-target mappings and dbt properties
• Lineage view and logical source traceability
• Catalogue integrations with Collibra, Atlan, Alation and Microsoft Purview

Integrations and automation

• Git and DevOps: GitHub, GitLab, Bitbucket, Azure DevOps, AWS CodeCommit
• dbt, Confluence, Jira, Slack, iFrame embedding, REST API and an MCP server
• Single sign-on with Google Workspace (with SCIM), Microsoft Entra ID and AWS IAM Identity Center

How it runs

• Browser only, hosted on AWS; no desktop application
• Optional customer-hosted or regional storage, customer-managed keys and private networking
• SOC 2 Type II, audit logs and IP access management

Pricing

Price on request

Priced per user, by quote: the vendor publishes no prices, tiers or trial length. It states that every feature is included at any price ("no tiers to unlock, no add-on modules"), with single sign-on and customer-hosted storage marked optional, premium support charged extra, and AI copilot credits billed on use. You can model in the browser without signing up, but cannot save the project until you do.

Vendor pricing page →

Demos and videos

• AI-powered data modelling: SqlDBM Copilot live demo Product demo · YouTube
• Data model governance in practice: creating and enforcing standards Webinar or talk · YouTube
• SqlDBM channel Channel or playlist · YouTube

About SqlDBM

SqlDBM is a privately held software company selling a single product, the data modelling platform of the same name. It publishes no "about us" page, so its founding year, head office and ownership are not stated on its own site; the company's LinkedIn page lists 2017 and San Diego, California. Its careers page describes a small team shipping weekly against "a much bigger incumbent". Kent Graziano and Gordon Wong are named publicly as advisers. Funding has not been published.

sqldbm.com