The Top ETL Tools for 2024

There are many extract, transform, and load tools, and the market continues to grow. Here’s a quick rundown of this year’s top offerings.

John Edwards, Technology Journalist & Author

January 8, 2024

4 Min Read
Conceptual display Data Extraction. Business concept act or process of retrieving data out of data sources
Niall Wiggan via Alamy Stock

Extract, transform, and load (ETL) tools provide a way to extract data from a system, transform it, and load it into a target repository. In practice, an ETL pipeline essentially serves as a data pipeline for cleaning, enriching, and transforming data from a variety of sources before integrating it for use in data analytics, business intelligence and data science applications.

Competition in the ETL field has intensified over the past few years with lots of newer, lightweight alternatives challenging the traditional stalwarts, such as offerings from Informatica, IBM, and Oracle says Dries Ballerstedt, a principal consultant with global technology research and advisory firm ISG in an email interview.

In today’s data-driven world, businesses are increasingly relying on ETL tools to efficiently manage and analyze large datasets, observes Adhiran Thirmal, solutions engineer at security products and services firm Security Compass via email. “Choosing the right ETL tool is crucial for ensuring data integrity, security, and compliance.”

Finding an appropriate ETL tool depends on its user’s specific needs and requirements, Thirmal says. “By carefully considering [both options], you can choose the tool that will help you efficiently manage and analyze your data, ultimately securing your data and achieving your business goals.”

Related:10 IT Trends to Watch for This Year

If you’re looking for this year’s leading ETL tools, here are 10 top offerings to consider.

1. offers a strong combination of power, connectivity, security, and ease of use, Ballerstedt says. Most competitors either lack popular features, are too complex for citizen data scientists, or don’t possess the connectivity needed for a modern data ecosystem with multiple sources and data sinks, he observes.

As a cloud-based platform, is known for its user-friendly interface, powerful features, and robust scalability, says Hataish Kumar, an e-commerce business leader and entrepreneur via email. “It boasts a wide range of pre-built connectors for various data sources and destinations, making it easy to integrate data from virtually any source,” he notes. “Additionally, its visual data mapping interface simplifies data transformation processes.”

Thirmal cautions that some small organizations may find to be an expensive tool with only limited customization options.

2. Airbyte

Airbyte is an open-source ETL tool that’s gained immense popularity in recent years. “It’s known for its flexibility, affordability, and community-driven development,” Kumar says. He adds that Airbyte offers a wide range of pre-built connectors and allows users to contribute and share their own connectors, expanding its data integration capabilities.

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3. StreamSets

With both open-source and commercial options, StreamSets offers scalable, real-time data integration, and strong data governance and security features. But watch out for its steep learning curve and complex integration and management functions, Thirmal warns.

4. Fivetran

Fivetran specializes in reverse ETL, a process that pushes data from data warehouses back into operational systems. This attribute makes it particularly valuable for organizations that need to activate their data in various tools and platforms, Kumar says. Fivetran also offers pre-built connectors for various SaaS applications and provides robust data quality checks.

5. Rivery

Cloud-based Rivery is focused on self-service data integration. “Its visual interface and intuitive workflows make it easy for business users to build their own data pipelines without relying on IT expertise,” Kumar says. Rivery also offers pre-built templates for common data pipelines and allows for custom scripting for more complex transformations.

6. Talend

Talend is available in open-source and commercial versions, with both offering a wide range of features, scalability, and strong community support. Beginners should be prepared for a steep learning curve, however, as well as a complex interface and potential compatibility issues, Thirmal warns.

Related:10 AI Startups to Watch

7. Informatica PowerCenter

An enterprise-grade solution, Informatica PowerCenter offers high performance, robust data security and compliance features, and extensive data management capabilities. On the downside, PowerCenter is expensive, can be complex to implement and manage, and allows only limited customization, Thirmal cautions.

8. Stitch

Stitch offers a cloud-based, user-friendly interface along with real-time data integration and extensive data transformation capabilities. Thirmal cautions, however, that adopters will have to live with limited support for on-premises data sources, Stitch can also be expensive when handling large datasets.

9. Hevo Data

Cloud-based and affordable, Hevo Data provides real-time data integration and pre-built connectors to various data sources. Adopters, however, will encounter limited data transformation capabilities, and the offering may not be suitable for complex data pipelines, Thirmal warns.

10. Matillion

Matillion supplies cloud-based, scalable, robust data transformation capabilities, as well as strong data security and compliance features. Yet the offering is expensive, complex to implement and manage, and provides only limited support for on-premises data sources, Thirmal cautions.

Changing Times

Two key trends are occurring now, and will likely continue into 2024, Ballerstedt predicts. “After several years with individual coded data pipelines, low/no-code is coming back to data integration,” he states. “In addition, AI adoption will dramatically change the way data pipelines are built.” Ballerstedt also believes that logical data integration is here to stay, giving ETL providers tough competition going forward.

About the Author(s)

John Edwards

Technology Journalist & Author

John Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.

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