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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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Top Reverse ETL Software Companies

Showing 10 of 2 companies ranked by annual revenue.

1
primeNumber Inc.

品川区, 東京都, Japan

primeNumberは「あらゆるデータを、ビジネスの力に変える」データテクノロジーカンパニーです。企業のデータ活用における不自由をなくし、人とAIが共存していく時代に、誰もがデータの価値と共にある世界を実現します。 primeNumberの「TROCCO」は、2,000以上の企業・団体に導入されているクラウドETLサービスです。ETL(データ転送・データ変換)機能に留まらず、ワークフロー機能、権限管理など、データ基盤の構築や運用に必要な機能を備えています。TROCCOで、データ利活用における一連のデータエンジニアリングプロセスを自動化し、お客様のデータ活用を支援します。 「COMETA」は、データの「意味(=メタデータ)」を管理・可視化し、データを整備するAIデータプラットフォームです。あらゆる利用者やAIが、組織内に蓄積された膨大なデータから必要なものを瞬時に発見・活用できる環境を提供します。 独自のAI技術により、従来手作業で行っていたメタデータ整備を大幅に効率化。メタデータの品質を継続的に維持し、組織の誰もが本当に信頼できるデータへ辿り着ける環境を構築することが可能です。

Revenue
$9.6M
Customers
-
Year founded
2015
Funding
-
Team size
87
Growth
-
2
Meiro

Singapore, Singapore

Meiro is an AI-powered, composable Customer Data Platform for Private Installations on Cloud & On-Premise—built for enterprises that require full control over their customer data and infrastructure. 👉🏼 Headquartered in Singapore with R&D in Central Europe 👉🏼 Received $3M in pre-Series A funding in January 2024. 👉🏼 Listed as one of the Top 10 Singaporean Big Data Companies in 2023. Unlike traditional SaaS CDPs that store customer data in their own cloud environments, Meiro is deployed privately—within your infrastructure—on any major cloud platform or on-premise, anywhere in the world. This ensures your data remains compliant, secure, and exactly where it belongs: under your IT team’s control. At the same time, Meiro unifies customer data from every touchpoint into a single, real-time view, enabling marketing teams to create personalized, cross-channel experiences that drive customer engagement and lifetime value. With built-in AI tools, marketers can predict behavior, segment audiences intelligently, and automate personalized journeys—without relying on engineering support. With Meiro, IT teams get the control they need and marketers the agility they expect—helping both teams unlock the full value of customer data, securely and at scale.

Revenue
$6.5M
Customers
-
Year founded
2017
Funding
-
Team size
59
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.