What is Reverse ETL? A Definition

Reverse ETL Defined

Reverse ETL moves data from your data warehouse and sends it to your business applications. The data in your warehouse is clean, processed, accurate, and complete, and ensures all your applications — and the business functions that use them — are working from the same high-quality dataset.

Reverse ETL can refer to both the process of moving this data, as well as the software tools that do the work. While this work has typically been performed manually through data requests sent to IT, robust reverse ETL products have been emerging that automate this process.

Who needs reverse ETL?

Many modern organizations keep their data in warehouses and deploy a large number of applications. Among those, many can’t commit the resources and expertise needed to manually build and maintain the pipelines they need. These organizations would benefit from a reverse ETL tool that automates as much of the process as possible.

However, organizations that prefer to build their own pipelines — and are willing to commit the resources needed to do so — may not need a reverse ETL tool. Smaller organizations also might not need a reverse ETL tool, because they don’t store or move enough data to require one.

Can reverse ETL be monitored?

Reverse ETL processes and tools are often monitored to make sure they are working to expectation and delivering the right data to the right systems at the right times.

Organizations can set up automatic flags, alerts, and notifications that trigger when an issue occurs, such as failed syncs, conversion, mapping, or other fundamental errors.

What is the difference between ETL and reverse ETL

ETL and reverse ETL are often confused. They follow the same process, and the main difference is which direction the data moves. In ETL, data moves from business applications and other sources to the data warehouse, in reverse ETL data moves from the data warehouse to business applications or other destinations.

Specifically, in the standard ETL process raw data is extracted from a source.

1. With ETL, data is extracted from a raw source where it is generated or is being stored. This source can be anything from an application to a website, to an excel file storing third party data purchased from an external entity.

2. That data is then transformed and made ready for storage. At this stage the data can be cleaned, de-duplicated, aggregated, reformatted, or otherwise changed to meet the storage requirements of the data warehouse, and/or any specific requirements from the organization.

3. Finally, the data is loaded into the data warehouse or other destination where it will be stored for use in business applications. Once the data is stored, it will require some form of reverse ETL to return to a usable form within a business application.

In sum: Reverse ETL and ETL is not an either/or — organizations need both processes. One brings data to a warehouse, and the other takes data from the warehouse and brings it to applications, leading to different reverse ETL and ETL use cases.

Reverse ETL Alternatives

Reverse ETL tools are not the only way to move data from the data warehouse to applications, but they are often the most efficient option. Other alternatives include:

• Manual transfers: A member of IT manually goes into the data warehouse, finds the required data, downloads it, and uploads it directly to the application.
• Custom integrations: Individual point-to-point pipelines are built for every application that needs access to data in the data warehouse.
• CDP or integration platform as a service (iPaaS): They use pre-built connectors to move data, but offer limited functionality and customization.

There are use cases where these alternatives may be a better choice than reverse ETL. However, reverse ETL offers the best combination of customization, efficiency, and scalability for creating the countless data pipelines modern organizations need.