10 Best ETL Testing Automation Tools In 2023

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.