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With so many different ETL testing automation tools available, figuring out which is right for you is tough. You know you want to facilitate and automate the testing of ETL processes in data warehousing but need to figure out which tool is best. I've got you! In this post I'll help make your choice easy, sharing my personal experiences using dozens of different ETL testing automation software with a variety of teams, with my picks of the best ETL testing automation tools.

What Are ETL Testing Automation Tools?

ETL testing automation tools are software that automate the testing process of ETL (Extract, Transform, Load) operations in data warehousing. These tools verify the accuracy and integrity of data as it is extracted from various sources, transformed, and then loaded into a target system like a data warehouse or database. They automate tasks such as data validation, transformation checks, and data loading verification.

The benefits and uses of ETL testing automation tools include enhancing the accuracy and efficiency of the ETL process. By automating repetitive and complex testing tasks, these tools reduce the likelihood of human error, ensuring data integrity and quality. They save time and resources in testing large volumes of data and help in early identification and resolution of data issues. This leads to more reliable data storage and reporting systems, which are crucial for data-driven decision-making in businesses.

Overviews Of The 10 Best ETL Testing Automation Tools

Here’s a brief description of each of the ETL testing automation tools to showcase each tool’s best use case, some noteworthy features, and screenshots to give a snapshot of the interface.

Best no-code ETL testing automation tool

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Rating: 4.3/5

RightData is an automated ETL test validation tool that enhances data readiness through data quality assurance. As a self-service cloud solution, its automated validation and reconciliation abilities foster continuous data quality control, along with data integrity and audit capabilities.

In addition to typical features like providing email notifications, it includes exception reporting vital for SOX proof of compliance.

RightData allows you to build data connections across various source systems and query chains. It provides over 150 connectors for applications, flat file data sources, cloud platform technologies, and databases. It makes activities like configuring batch job scheduling and reconciliations a breeze to execute.

RightData is a tool for enterprises that need to connect to multiple data targets and data sources to perform core ETL functions. Especially those who routinely have to reconcile high volume, high complexity data from different models and data types.

RightData provides a free demo. Pricing is available upon request.

Best for rapid, high-volume data testing

  • 15-day free trial
  • Pricing upon request
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Rating: 4.4/5

QuerySurge is a highly intuitive and robust data testing solution for automating the testing and validation of data warehouses as well as the ETL testing process. It is effective at making sure any data extracted from various sources remains uncorrupted and intact in the target data warehouse. The software achieves this successfully by analyzing the data and identifying any variations quickly and efficiently.

One of the key functions of QuerySurge ETL testing involves the point-to-point testing process. It mimics the ETL development process by performing tests on a point-to-point basis, along the data warehouse lifecycle. This approach is capable of delivering up to 100% coverage of data mapping, making the software one of the best ETL testing automation tools for QA teams.

QuerySurge supports a wide variety of test types across more than 200 data stores, seamlessly connecting to various databases and warehouses, files and APIs, CRMs and ERPs, big data and NoSQL data stores, as well as ecommerce, marketing and accounting software. Pricing for QuerySurge data validation and ETL testing software starts from $11,493 per full user for the perpetual license package or $5,747 per user for the subscription option with a minimum of two full users.

Best vendor-agnostic, DataOps platform for end-to-end testing of data-centric processes

  • Free trial + free demo available
  • Pricing upon request
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Rating: 5/5

iCEDQ follows a rule-based approach that facilitates the automating of ETL testing and other processes like production data monitoring, snowflake migration testing, and cloud data migration testing. The platform allows you to use iCEDQ’s inbuilt scheduler to trigger ETL testing business rules, if necessary, with an external scheduler.

It excels in the left-shift approach enhanced by its unique in-memory engine. This allows iCEDQ to efficiently compare and validate the full volume of data in memory. This makes it capable of supporting files and databases of all sizes. In addition, it also supports APIs and software languages such as Java, SQL, and Apache Groovy.

iCEDQ comes with a regression suite and advanced scripting. Its DataOps implementation is enhanced by its integration with DevOps, GIT, scheduling, and CI/CD tools like DataStage and Jenkins. Encryption and advanced role-based access control capabilities are also available.

Pricing is available upon request.

Best for accommodating various data types, data sources, and huge data volumes

As its name implies, ETL Validator is used for validating ETL during the process of data migration and integration. It has baselining capabilities and allows users to compare and analyze data schemas across different environments.

ETL Validator aims to reduce costs and minimize testing effort and overhead. It includes a Tomcat server and an embedded PostgreSQL repository. Its automated testing encompasses various types of data and data sources, like NoSQL, flat files, relational databases, and Big Data sources.

It possesses an inbuilt ETL engine that performs automation testing. This automation enables the extraction and comparison of millions of records from multiple data sources while simultaneously executing test cases.

For ease of use, it provides a drag-and-drop visual test case builder. It also doesn’t require any custom programming and yet increases business productivity.

ETL Validator is good for those who need to share test results across platforms and data types.

ETL Validator offers a demo and a 30-day free trial. Pricing is available upon request.

Best intuitive, feature-rich testing platform for both structured & unstructured data

DataQ enables organizations to reduce their ETL failures, making it easy to apply transformation logic to match the schema of the destination database warehouse. DataQ automates the primary phases in the ETL process, from code development (you can get started with as little as 10 lines of YAML code), transformation testing, data mapping, and so on.

It makes complex data management possible, supporting both on-premise and multi-cloud architecture. DataQ is also capable of auto-detecting key columns across source and destination databases.

DataQ allows you to connect to multiple data sources and file formats, including popular ones like PostgreSQL, Oracle, Apache Hive, Microsoft SQL Server, MongoDB, MySQL, and destination DB warehouses such as Cassandra, Hadoop, and Hive.

To keep costs low for users, DataQ optionally offers AI-based optimization of computing resource utilization.

DataQ provides three plans, namely: Starter, Business, and Enterprise. The Starter is a free plan that’s ideal for a single user. The Business plan is ideal for startups and small organizations and comes with unlimited users. The Business plan includes everything in the Starter plan plus features like anomaly detection, cloud or on-premise hosting, and priority support, among others.

The Enterprise plan is designed for medium to large businesses. In addition to containing everything in the Business plan, it offers customers multiple DataQ endpoints, customer profile metrics, advanced and unlimited quality rules, and much more.

Pricing is provided upon request.

Best for rapid development of digital products through exploratory testing

  • Its Professional plan is priced at 29 Euros/user (up to 100 users)/month

TestBench is a multifaceted testing solution built for a wide variety of users such as testers, test managers, product owners, and agile teams. Its content translation capabilities further boost collaboration across global teams so they can manage projects in real-time.

It offers a smart load testing hub for controlling data-driven tests, whether manual or automated. It allows teams to build and execute predefined test cases immediately. This allows the teams to subsequently compare the outcome with previous test results.

TestBench provides users with both data-driven and keyword-driven interaction methods to facilitate exploratory testing. It also includes data-driven extensions to enable them to create test cases in several variations. TestBench also adapts to your toolchain with APIs that integrate with other third-party applications such as Jira.

TestBench is ideal for organizations that develop or intend to build high-quality digital products through efficient and effective testing.

TestBench has a free option that provides basic features for up to five users. Its Professional plan is priced at 29 Euros per user (up to 100 users) per month. Pricing is available upon request for its Professional Plus tier.

Best suite of intelligent governance, analytics, and Big Data services

  • 30-day free trial
  • Pricing upon request

Informatica Powercenter is a top ranked data integration and data visualization solution. Although it is often compared to Informatica Cloud Data Integration. Informatica PowerCenter is more ideally suited for large enterprises that can utilize various features and options. As a powerful ETL tool, Informatica Powercenter is designed to help organizations unleash the value of their data. Its end-to-end data integration functionalities provide companies with incredibly fast data integration and data replication tools. Informatica Powercenter boasts a broad set of features that make it possible to integrate fragmented, disparate, and raw data from different sources, eventually transforming it into high-quality data that is business-ready.Informatica Powercenter enables users to create workflows that can be used to monitor and identify bugs in data systems. Informatica Powercenter’s data integration life cycle capabilities build operational confidence in data and data integration projects. The software is also good for enterprise scalability.Informatica Powercenter pricing is available upon request.

Best data analytic testing tool capable of quickly identifying errors in the ETL process

Codoid’s ETL Testing Services offers data analytical services with high-end automation testing tools and capabilities. The data validation it offers includes spot checks between target and actual data, providing counts and aggregate values.

It can work with various heterogeneous sources such as spreadsheets, relational databases, and CSVs, to validate their data quality. Its test coverage also encompasses navigation/GUI testing and is compatible with various proprietary and open-source tools.

Codoid’s ETL also performs automated testing services such as metadata testing, including testing for data completeness and corruption. During this process, it verifies data lengths, data types, and indexes.

Codoid’s ETL testing is suited for those who need to mitigate bad data with quality testing, identify syntax issues or expose errors due to incorrect reference types.

Pricing is available upon request.

Best comprehensive solution for orchestrating workflows and building ETL pipelines at scale

  • $1.20/RPU credit

Rivery manages your data for you so you can focus on your business. It is designed for both developers and those with little technical expertise. It provides no-code execution for complex data challenges, accomplishing tasks with just a few clicks. On the other hand, it has an inbuilt native Python language for flexibility and customization.

Rivery empowers business productivity with its version control repository. It also combines, consolidates, and transforms data right inside a cloud data warehouse. This makes Rivery agile and primed for hyper scalability, with multiple deployment environments.

It is built for integration with a vast number of varied data sources, with over 190 out-of-the-box, pre-built data connectors such as various CRMs, databases, analytic, and marketing tools.

Rivery has three pricing options, along with a pricing calculator to estimate usage-based pricing. Each option is priced at units called Rivery Pricing Unit (RPU) credit.

Its Starter plan is created for small Business Intelligence (BI) and data teams to build pipelines and orchestrate workflows. It is priced at $0.75 per RPU credit.

The Professional plan is designed for advanced data teams who have the requisite engineering capabilities. In addition to everything offered in the Starter plan, the Professional plan offers role-based access control, three distinct environments, and the ability to run Python code. It is priced at $1.20 per RPU credit.

The Enterprise plan is customizable and its pricing is available upon request.

Best built-in tool with a business rules engine (BRE)

  • 30 Days Free Trials

Bitwise QualiDI was designed as a solution to manual and error-prone ETL testing, especially to eliminate reliance on visual comparisons of source to target mappings. It does this by providing a central repository, which in turn, automates the validation process. Moreover, it allows QA teams and developers to evaluate automated ETL testing with their own datasets.

QualiDI provides a built-in tool that generates complex queries for fast transformations known as a business rules engine (BRE). This accelerates testing for non-technical users who are allowed to write business rules instead of queries.

QualiDI eliminates the risk of using sensitive production data in test environments. It does this by seamlessly integrating with Bitwise Test Data Management (TDM) Suite to provide testers with production-like test data that is compliant.

QualiDI is ideal for businesses who want an enterprise-wide, end-to-end platform for operating centralized testing. This is especially useful for companies that need to transform data sets from various operational systems with large data volumes into a data warehouse.

It comes with a 30-day free trial that provides access to basic features that enables QA teams to run test cases.

The Best ETL Testing Automation Tools Summary

Tools Price
RightData No price details
QuerySurge Pricing upon request
iCEDQ Pricing upon request
ETL Validator No price details
DataQ No price details
TestBench Its Professional plan is priced at 29 Euros/user (up to 100 users)/month
Informatica Powercenter Pricing upon request
Codoid’s ETL Testing Services No price details
Rivery $1.20/RPU credit
Bitwise QualiDI No price details
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How I Selected the Best ETL Testing Automation Tools

If you're wondering how I selected the best ETL testing automation tools, here's where I'll break it all down for you. First of all, I started with tools that automate ETL testing that have high user review and satisfaction ratings. Then, using my experience in QA testing, I discerned what key criteria were most important for ETL testing automation tools and compared how each of them stacked up against the rest.

I empathize with how much time it takes to source the right software for a job. I do this work so that you don't have to. I've been using and reviewing tools that automate ETL testing for years so you can trust me to do the heavy lifting and compile all the facts you need to make your final decision.

Selection Criteria

After careful consideration, I've determined that these are the most important criteria when selecting the best tools that automate ETL testing. Here's a brief list outlining the whats and whys of my selection.

User Interface (UI) 

ETL testing requires several steps of execution. So, its user interface should simplify the multi-level process such that it can be completed in as few clicks as possible, with clarity and minimal hassle.


The user experience should promote easy navigation for testing functionality. Other elements should feel intuitive and simple, such that the time taken to implement ETL tests is drastically reduced. 


ETL testing is implemented by data engineers working across various domains and use cases. As a result, its results and operations frequently require integration with other tools, so integration should be a strong suit. 


A good product should balance cost-effectiveness and quality if its use is to remain sustainable for the majority of its customers. Hence, a product’s pricing regimen factored into my selection.

People Also Ask

Here are a few questions I thought of that I wanted to address while writing this article. Hopefully, they prove beneficial to you and tie up any loose ends.

What are the key benefits of ETL testing?

There are several key benefits of ETL testing, including:

  1. Improved data quality: ETL testing helps to ensure that data is accurate, complete, and consistent across different systems, which can improve decision-making and reduce errors.
  2. Increased efficiency: By automating the testing process, ETL testing can save time and resources, allowing teams to focus on other critical tasks.
  3. Risk mitigation: ETL testing can help to identify potential issues early in the process, reducing the risk of data loss, downtime, or other costly problems.
  4. Compliance: ETL testing can help organizations comply with regulatory requirements by ensuring that data is accurately and securely processed.
  5. Improved collaboration: ETL testing can help to improve collaboration between teams by providing a common framework and language for data processing and analysis.

What are ETL testing automation key features?

  1. Data validation and reconciliation: Effective validation of data transformations with strict adherence to compliance and business rules.
  2. Automation for workflow integration: Provide an automation testing toolkit to eliminate manual procedures in the ETL testing process, so efficiency and productivity gains are increased.
  3. Data validation and comparison engines: Provide the ability to both compare and seamlessly validate high volumes of data spanning multiple databases for accuracy and quality. It should be capable of performing this with files of different types and formats.
  4. Data connectors: A comprehensive ETL automation testing tool should be capable of supporting third-party, native integration with APIs, files, and databases.
  5. Support for ETL testing infrastructure: This includes support for relevant ecosystems and architecture like ETL server/staging areas, data warehouses, and unstructured data.

What other testing resources do I need?

If you’re thinking about ETL testing automation, these additional resources may complement your research:

The Importance Of ETL Testing Automation Tools

Data management, especially the refined and well-targeted type, is a huge competitive advantage. Therefore, businesses require more of it than ever before. ETL automation tools play a huge part in making sense of our digital age’s exponential data surge. This is because ETL is a vital process for aggregating data into a central repository to facilitate its effective analysis. 

So, what do you think about this list? Kindly give us your feedback in the comments below. And while you’re at it, subscribe to the QA Lead newsletter to get more informative topics. 

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By Eze Onukwube

Eze has a master's degree in communications with over 10 years of experience as a software engineer. His playground is at the intersection of technology, process improvement, and simplifying IT concepts.