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Top 30 Reverse ETL Software SaaS Companies in May 2026

As of May 2026, there are 30 SaaS companies in Reverse ETL Software. They have combined revenues of $795.2M and employ 5.5K people. They have raised $1.4B and serve 18K customers combined.

Reverse ETL software enables organizations to extract transformed, business-ready data from data warehouses and move it back into operational systems such as Customer Relationship Management (CRM) tools, marketing platforms, and support applications. This process supports seamless data flow between analytics and business operations, ensuring that teams have access to relevant insights in real-time. The primary use cases for reverse ETL include enriching customer profiles, optimizing marketing campaigns, and enabling data-driven decision-making across various departments. This software typically features data synchronization capabilities, user-friendly interfaces for setting up data pipelines, and monitoring tools to ensure data integrity and accuracy as it flows into different applications. Common buyer personas for reverse ETL solutions include data analysts, marketing professionals, sales operations teams, and IT departments. These users require reliable access to cleaned and structured data in the systems they utilize every day, thereby enhancing their operational efficiency and enabling better engagement with customers and prospects.

Companies
30
Revenue
$795.2M
Funding
$1.4B
Employees
5.5K

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Sorting: Highest -> Lowest

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Top Reverse ETL Software Companies

Showing 10 of 2 companies ranked by annual revenue.

1
Fivetran

Oakland, California, United States

data integration platform

Revenue
$300M
Customers
6.3K
Year founded
2012
Funding
$727.4M
Team size
1.7K
Growth
-
2
Workato

Mountain View, California, United States

Workato's platform provides businesses with a flexible and scalable way to automate their workflows

Revenue
$150M
Customers
11K
Year founded
2013
Funding
$415M
Team size
1.3K
Growth
-

Inclusion Criteria

- The software must facilitate the extraction of data from data warehouses. - It must enable the loading of this data into operational systems used by businesses. - The solution should support real-time data availability for end-users in various applications. - It must handle data transformation to ensure only business-ready data is processed and shared. - The solution is not just for data warehousing; it must integrate with diverse business applications such as CRM, marketing tools, and support systems. - The product should provide tools for monitoring data flows and ensuring data accuracy.