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Top 7 Data Fabric Software SaaS Companies in May 2026

As of May 2026, there are 7 SaaS companies in Data Fabric Software. They have combined revenues of $1.6B and employ 9.2K people. They have raised $1.7B and serve 13K customers combined.

Data Fabric Software provides a cohesive data management framework that integrates disparate data sources across various platforms and environments. It enables organizations to efficiently access, manage, and analyze their data in real time, promoting a unified view of data assets regardless of where they reside. This approach streamlines data workflows and enhances data governance, making it easier for businesses to comply with regulations and maintain data quality. The primary use cases for Data Fabric Software include data integration, data governance, and data accessibility. It offers features such as data virtualization, data cataloging, and automated workflows, which help organizations improve decision-making processes and support analytics. Typical users of these solutions include IT teams, data analysts, and data engineers who require real-time data access and management capabilities for operational and strategic needs.

Companies
7
Revenue
$1.6B
Funding
$1.7B
Employees
9.2K

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Top Data Fabric Software Companies

Showing 10 of 1 companies ranked by annual revenue.

1
Stae

Detroit, Michigan, United States

Provider of a digital infrastructure platform designed to offer open access to the world's civic data in one place, in real-time and with a uniform API. The company's digital infrastructure platform offers universal tool for data management and collaboration, integrate data from any source, map different data types and create real-time data feeds, enabling city managers to city workers to make better data-driven decisions, drive performance and manage vendors.

Revenue
$23.5M
Customers
-
Year founded
2016
Funding
$3M
Team size
53
Growth
14.59%

Inclusion Criteria

- Must provide seamless integration across multiple data sources and environments - Should enable real-time data access and analytics capabilities - Must include features for data governance and compliance - Should support data virtualization and automated workflows - Not just offer data storage solutions; must also facilitate data management and usability improvements - Must cater to both structured and unstructured data types - Should include tools for data quality assessment and monitoring