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Develop Databases Online

without writing a single line of code

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Powering modern frameworks
and methodologies

Data Warehouse & Data Lake
Data Mesh Framework
Data Vault Methodology
Latest Snowflake features
Support for the latest features like Snowflake’s VARIANT datatype for semistructured data, views, and column lineage allows users to go beyond pure relational modeling.
Model and present
SqlDBM diagrams are living interactive documents that allow users to present their designs in real-time at any level of detail - from conceptual to physical - and generate the DDL, alters and YAML.
Views, functions and procedures
In our diagrams, objects such as views and procedures can live alongside physical tables to provide insight into data pipelines and transformations at the heart of a data warehouse.
Subject areas
Distributed teams can happily share the same database platform and organize themselves across projects using Subject Areas - keeping their diagrams separate while having global enterprise visibility. Comments and metadata is picked up automatically during the reverse engineering process and can be maintained via Excel by anyone in the organization.
Multiple projects and database platforms
Zhamak Dehghani first introduced the concept of a data mesh to overcome the ungovernability of Data Lakes and the bottlenecks of monolithic Data Warehouses. But distributed data teams can still take advantage of SqlDBM’s one-stop documentation and search across multiple projects and database platforms.
A sponsor of the WWDVC
SqlDBM is a strong supporter of the Data Vault community, a sponsor of the WWDVC conference two years running, and the modeling tool of choice during official Data Vault courses.
Hubs, links, satellites
SqlDBM’s templates, naming conventions, and logical to physical translations are built to ensure consistency and time savings in repeatable operations such as the creation of hubs, links, satellites, and bridge tables.
Colors and view modes
Colors and view mode options make it easy for users to find their way around expansive DV architectures and work with them at any level of detail. Automated DV templates and an object creation wizard are currently in the works and will be available soon, along with other exciting enhancements.

Premier Partner

Find us on the Snowflake Partner Connect

In 2019, SqlDBM became the first online modeling tool to support Snowflake projects and has continued to add support for Snowflake's latest objects, such as Views, Functions, and Procedures. The ability to natively modify, track, Reverse/Forward engineer Snowflake objects, and display them on a diagram is why over 300 Snowflake clients use SqlDBM.

Connect your favorite tools

Integration with web apps, Git repositories, and databases through secure native connectors.

Strategic Advisors

Meet the experts and industry thought-leaders helping shape the future of SqlDBM
Kent Graziano
The Data Warrior, Strategic Advisor, Data Vault Master, Author, Speaker, and Tae Kwon Do Grandmaster
See details
Gordon Wong
Leading organizations through analytics transformations, preference for social missions, healthcare, energy, education, and civic engagement
See details

Everything you need at your fingertips

By bringing your existing DB/DW to SqlDBM, you can automatically create a database model that will provide powerful and effective visualization. Make changes and generate new SQL scripts including Alter scripts.
Securely connect to cloud databases such as Snowflake and Azure Synapse directly from SqlDBM to browse schemas and retrieve DDL automatically.
Visualize sources, joins, transformations, and outputs in real-time at column level to understand complex views and DML logic quickly. Syntax to column highlighting in the editor and diagram allows users to track any field as it flows from the sources to final output.
Comments are read from DDL and available on a single screen where users can find and edit objects across the entire project. Flags help identify sensitive fields and can be used for tracking and filtering at the object or column level.
With unlimited revision history for every project, users can compare changes between any two save points and open and recover a project from a previous state. Users can instantly find any revision using labels, icons, and related filters.
Work concurrently and comment on any object tagging and alerting specific team members. View modes allow users of any technical level to view, explore, or develop a DB schema without converting the project.
Compare project revisions to live DB environments and generate ad-hoc alter scripts between them. Pair your project with any online git repository to automatically push alters or individual objects to new branches and pair with CICD tools like Schemachange or Flyway for fully automated deployments.
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Data management partner

Find us on the Azure Marketplace

SqlDBM supports Azure Synapse modeling with extended support for Views, Functions, Procedures, and more. Using SqlDBM's Virtual Suggested Relationships feature, Synapse customers can relationally link and explore their entire landscape without using foreign keys.

Developed for IT teams

SqlDBM helps develop or transition to leading cloud data warehouses, including Snowflake, Synapse, and Redshift. Whether migrating an existing enterprise data warehouse, data lake, or building one from scratch, SqlDBM's functionality is designed to meet the needs of BI professionals by providing users with cutting-edge capabilities.
An intuitive web-based interface lowers the technical barrier and lets all team members take advantage of data discovery and explore the data landscape.

From exploring business entities in a simplified conceptual view to flagging sensitive or critical fields and objects, all roles get to take advantage or contribute to project metadata without using SQL.
Like modeling in SqlDBM, change tracking and revision comparison is a simple, visual process that requires no prior knowledge of git. With Jira integration, project managers can tie model changes to Jira tasks for full audit history and synchronized comment thread.

Enterprise plan

SqlDBM's Enterprise plan allows users to go beyond modeling by offering integrations like Confluence for sharing and Jira for task management. Enterprise also unlocks team communication, alerts, and governance as well as time-saving features like view-column lineage and suggested relationships.
Natively connect SqlDBM to web service apps and database providers through secure single sign-on protocols.

Multimedia

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Security

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Customer stories

Hundreds of organizations worldwide use SqlDBM for enterprise modeling because it saves time, ensures consistent, error-free deployments, and integrates easily with the rest of the modern BI stack. Read about where our customers are finding success with SqlDBM and how they've come to depend on it for modeling, DevOps, and data discovery.
All stories
“During your first encounter with SqlDBM, you shouldn’t look at it as just another ERD tool. Well, at first glance most of us would surely agree that it stands out with its good looking, user friendly interface. What’s not to like here – that soothing-for-the-eyes dark theme with just enough vivid colours to stand out and show the structure and the possibility of seamlessly creating tables and defining relationships between them… without writing a single line of code.”
Ana Mikoš Ana Mikoš,
Marketing Assistant, In516ht
Katja Jurkovšek Katja Jurkovšek,
Consultant, In516ht
“Pandata Group has assisted many customers in their pursuit of digital transformation through effective data management. Our evolution towards pure cloud solutions such as Snowflake and Thoughtspot reflects the growth of the SaaS approach to data and analytics platforms. We have increased time-to-value by deploying zero-management solutions that support cloud DW and analytics (e.g. Matillion ETL).”
Joseph Caparula Joseph Caparula,
Senior Consultant, Pandata Group
“Most people know SqlDBM as a cloud-based data modeling tool. Intricity sees it differently: as a cloud migration tool with modeling capabilities that also generates documentation. Having performed countless migration projects, Intricity knows precisely where the pain points lie. Analyzing the on-premise database architecture, copying DDL by hand, and making the adjustments to convert it into Snowflake format.”
Rich Hathaway Rich Hathaway,
Senior Director, Data Architecture, Intricity

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