Best Data Modeling Tools for OpenMetadata
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Compare the Top Data Modeling Tools that integrate with OpenMetadata as of July 2025
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This a list of Data Modeling tools that integrate with OpenMetadata. Use the filters on the left to add additional filters for products that have integrations with OpenMetadata. View the products that work with OpenMetadata in the table below.
What are Data Modeling Tools for OpenMetadata?
Data modeling tools are software tools that help organizations design, visualize, and manage data structures, relationships, and flows within databases and data systems. These tools enable data architects and engineers to create conceptual, logical, and physical data models that ensure data is organized in a way that is efficient, scalable, and aligned with business needs. Data modeling tools also provide features for defining data attributes, establishing relationships between entities, and ensuring data integrity through constraints. By automating aspects of the design and validation process, these tools help prevent errors and inconsistencies in database structures. They are essential for businesses that need to manage complex datasets and maintain data consistency across multiple platforms. Compare and read user reviews of the best Data Modeling tools for OpenMetadata currently available using the table below. This list is updated regularly.
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1
Domo
Domo
Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results. -
2
Looker
Google
Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time. -
3
dbt
dbt Labs
Version control, quality assurance, documentation and modularity allow data teams to collaborate like software engineering teams. Analytics errors should be treated with the same level of urgency as bugs in a production product. Much of an analytic workflow is manual. We believe workflows should be built to execute with a single command. Data teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows. Built-in CI/CD ensures that changes to data models move appropriately through development, staging, and production environments. dbt Cloud also provides guaranteed uptime and custom SLAs.Starting Price: $50 per user per month -
4
Amazon QuickSight
Amazon
Amazon QuickSight allows everyone in your organization to understand your data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning. QuickSight powers millions of dashboard views weekly for customers such as the NFL, Expedia, Volvo, Thomson Reuters, Best Western and Comcast, allowing their end-users to make better data-driven decisions. Ask conversational questions of your data and use Q’s ML-powered engine to receive relevant visualizations without the time-consuming data preparation from authors and admins. Discover hidden insights from your data, perform accurate forecasting and what-if analysis, or add easy-to-understand natural language narratives to dashboards by leveraging AWS' expertise in machine learning. Easily embed interactive visualizations and dashboards, sophisticated dashboard authoring, or natural language query capabilities in your applications. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
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