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Modern advanced marketing analytics is hard to imagine without ETL and other data integration tools. After all, before a company starts building reports and searching for insights, all the data they collect from disparate sources must be processed using data integration tools: cleaned, verified, brought into a single format, and combined.
In this article, we detail the top 20 ETL software for 2025 so you can choose the best one for your business.
Note: This article was first published in 2023 and was thoroughly revised and updated in February 2025 to provide the most accurate and comprehensive information.
ETL stands for Extract, Transform, and Load. It is a vital data integration process aimed at consolidating information from diverse sources into a centralized repository.
The ETL process involves collecting data, applying standard business rules to clean and reform data in a proper format, and loading it to a data warehouse or database.
ETL (Extract, Transform, Load) is the data integration process that underpins data-driven analytics. It consists of three steps:
ETL provides the foundation for successful data analysis and a single source of truth to ensure that all enterprise data is consistent and up to date. This process ensures that data from various sources is unified, making it easier to analyze and derive actionable insights.
By leveraging ETL, businesses can streamline their data integration processes, ensuring that their data warehouse is populated with high-quality, consistent data.
ETL is a crucial step in preparing raw data for storage and analytics, especially in the marketing domain. It enables businesses to study raw datasets in a suitable format necessary for analytics and deriving meaningful insights.
ETL tools automate the data preparation and migration process, offering flexibility to set up periodic integrations or perform them during runtime. This allows businesses to focus on important tasks instead of carrying out mundane tasks of extracting and loading data.
By using ETL tools, marketers can ensure that their data is accurate, up-to-date, and ready for analysis, leading to better decision-making and more effective marketing strategies.
ETL tools or data integration tools are services that help you execute the Extract, transform, and load process. Simply put, ETL software allows companies to collect data of various types from multiple sources, convert it into a single format, and upload it to a centralized repository such as Google BigQuery, Snowflake, or Azure.
Let's consider types of ETL tools.
All ETL tools can be divided into four types depending on their infrastructure and the supporting organization or vendor. Some are designed to work in the local environment, some in the cloud, and others both locally and in the cloud.
Cloud-based ETL tools extract data from sources and load it directly into cloud storage. Many cloud-based ETL tools function as a serverless data integration service, offering scalability and ease of use without the need for managing server infrastructure. They can then transform this data using the power and scale of the cloud. This is a modern approach to the familiar ETL process, in which data transformation occurs after data is loaded into storage.
Traditional ETL tools extract and transform data from different sources before loading it into the warehouse. With the advent of cloud storage, there is no longer a need for data cleaning at an intermediate stage between the source and the target storage location.
Cloud-based ETL tools are especially relevant for advanced analytics. For example, you can load raw data into a data lake and then combine it with data from other sources or use it to train predictive models. Saving data in its raw format allows analysts to expand their capabilities. This approach is faster because it harnesses the power of modern data processing engines and reduces unnecessary data movement.
These are ETL tools developed by commercial organizations and are often part of larger analytics platforms. The advantages of enterprise ETL tools include reliability and maturity, as they have been on the market for a long time, and efficiently load data from various sources into data warehouses.
They may also offer advanced functionality: a graphical user interface (GUI) for designing ETL flows, support for most relational and non-relational databases, a high level of customer support, and extensive documentation.
In terms of minutes, enterprise ETL tools are usually more expensive than alternatives, require additional training for employees, and are difficult to integrate.
These free ETL tools offer a GUI for creating and managing data flows from any data source. Thanks to the open-source nature of these services, users can understand how they work and can extend their functionality.
Open-source ETL tools are a budget alternative to paid services. Some do not support complex transformations and may not offer customer support.
These are ETL tools that companies create themselves using SQL, Python, or Java. These custom solutions can be tailored to clean and format extracted data before loading it into the final storage destination. On the one hand, such solutions have great flexibility and can be adapted to business needs. On the other hand, they require a lot of resources for their testing, maintenance, and updating.
The following are the key features of ETL tools. Let's dive in.
Data extraction is the process of collecting and storing data from various sources, including databases, files, and APIs. ETL tools can extract data from multiple sources, including structured and unstructured data. They can also handle large volumes of data and provide features such as data filtering, data sorting, and data aggregation.
Data transformation involves converting raw data into a format that is suitable for analysis and reporting. ETL tools provide a wide range of transformation features, including data cleaning, standardization, enrichment, and aggregation.
They can also handle complex operations such as pivoting, merging, and splitting datasets. This step ensures that the data is consistent, accurate, and aligned with the organization's reporting requirements.
Data loading is the process of transferring transformed data into a target system, such as a data warehouse, data lake, or business intelligence platform. ETL tools support both batch and real-time loading, depending on the organization's needs. They can handle high data volumes while maintaining data integrity and consistency.
ETL tools offer robust automation and scheduling features, allowing users to define workflows and set up recurring tasks. This eliminates the need for manual execution of data pipelines, saving time and reducing errors.
With scheduling capabilities, businesses can ensure that their data pipelines run at predefined intervals, keeping their data up-to-date for reporting and analytics.
When choosing an ETL tool, you should consider your business requirements, the amount of data to be collected, the sources of that data, and how you will use it.
What to pay attention to when choosing an ETL tool:
Now that we have covered the types and features of ETL tools, let's take a look at the most popular of these tools.
There are a lot of ETL tools on the market to help you simplify your data management while also saving you time and money. Let's take a look at some of them, starting with the best ETL tools and software
It is a no-code ETL/ELT digital analytics platform that simplifies data management and reporting. The OWOX BI platform allows you to collect marketing data for reports of any complexity in secure Google BigQuery cloud storage.
OWOX BI automatically collects raw data from various sources and converts it into a format that's convenient for building reports. You will receive ready-made data sets automatically transformed into the necessary structure, taking into account the nuances of data accuracy that are important for marketers.
You won't need to spend time developing and maintaining complex transformations, delving into the data structure, and identifying reasons for discrepancies. OWOX BI frees up your precious time so you can pay more attention to optimizing advertising campaigns and growth areas.
When you rely on OWOX BI, you no longer need to wait for reports from an analyst. Based on simulated data, you can get ready-made dashboards or customized reports that are right for your business.
Due to OWOX BI's unique approach, you can change data sources and data structures without rewriting SQL queries or changing the order of reports. This is especially relevant with the release of Google Analytics 4.
Sign up for a demo to learn more about the OWOX BI value for your business.
AWS Glue is Amazon’s serverless data integration service that makes it easy to discover, prepare, move, and integrate data from multiple sources for analysis, machine learning, and application development.
Azure Data Factory is Microsoft’s cloud-based ETL service for scalable serverless data integration and transformation. Azure Data Factory supports integration with various data warehousing solutions, making it easier for organizations to manage and analyze their data. It offers a no-code user interface to create, monitor, and manage data flows intuitively.
Dataflow is a cloud-based ETL data transfer service from Google that allows you to process both streaming and batch data and efficiently load data into various destinations without requiring you to own a server.
Integrate.io is an ETL data integration platform designed specifically for e-commerce projects. It allows you to process data from hundreds of sources using various methods (Integrate.io ETL, Reverse ETL, API Management). It offers an intuitive, no-code interface to make it easier for non-technical people to work with data streams.
PowerCenter is a high-performance enterprise data integration platform developed by Informatica. The company also has a cloud-native ETL and ELT solution called Cloud Data Integration.
Oracle Data Integrator is an enterprise ETL platform for building, deploying, and managing complex data warehouses. The tool loads and transforms data into a data warehouse using the capabilities of the target database instead of relying on a regular ETL server.
Pre-built connectors simplify data integration workflows by automating the manual integration tasks required to connect databases and big data.
SAP Data Services is enterprise data management software. The tool allows you to extract data from any source as well as transform, integrate, and format this data into any target system or database. You can use it to create data marts or data warehouses of any kind.
IBM DataStage is a data integration tool that helps you design, develop, and execute data movement and transformation tasks. DataStage supports both ETL and ELT processes. The base version is for local deployment. However, a cloud version of the service is also available, called IBM Cloud Pak for Data.
SQL Server Integration Services is an enterprise ETL platform for data integration and transformation. It allows you to extract and transform data from sources such as XML files, flat files, and relational databases, then load it into a data warehouse. Because it is a Microsoft product, SSIS only supports Microsoft SQL Server.
Talend Open Studio is free open-source integration software that helps turn complex data into understandable information for decision-makers. This simple and intuitive tool is widely used in the US. It can easily compete with products by other major players.
With TOS, you can start building basic data pipelines in no time. You can perform simple ETL and data integration tasks, get graphical profiles of your data, and manage files from a locally installed open-source environment.
Pentaho Data Integration (formerly known as Kettle), is an open-source ETL tool owned by Hitachi. The service has several graphical user interfaces for creating data pipelines. Users can design tasks and data transformations using the Spoon PDI client and then run them using Kitchen.
Apache Hadoop is an open-source platform for processing and storing large amounts of data by distributing the computing load across computing clusters. The main advantage of Hadoop is scalability. It seamlessly transitions from running on a single node to thousands of nodes. In addition, its code can be changed according to business requirements.
Skyvia is Devart's all-in-one cloud data platform for all data integration capabilities for, management, backup, and data access.
Skyvia Data Integration is a no-code ETL and ELT tool for various data extraction and data integration scenarios. It works with CSV files, databases (SQL Server, Oracle, PostgreSQL, MySQL), cloud storage (Amazon Redshift, Google BigQuery, Snowflake), and applications (Salesforce, HubSpot, Dynamics CRM, and many more).
Jaspersoft ETL is Jaspersoft's open-source software that is data and architecture agnostic. This means you can connect to data from any source and work with it anywhere: on-premises, in the cloud, or in a hybrid environment. In addition, you can make changes to the Jaspersoft source code according to your needs.
The Jaspersoft tool is part of the Jaspersoft Business Intelligence suite, which offers a customizable, flexible, and developer-friendly business intelligence tools and platform.
Hevo Data is a no-code data pipeline platform that enables seamless movement of data from multiple sources to data warehouses in real-time. It simplifies the process of extracting, transforming, and loading (ETL) data by providing a user-friendly interface and automated workflows.
With support for over 150 data sources, Hevo Data allows businesses to integrate data without writing any code, ensuring reliable and consistent data for analytics and decision-making.
SAS Data Management is a comprehensive data integration and management tool designed to handle complex data challenges. It enables businesses to access, integrate, cleanse, and govern data across multiple sources, ensuring consistency and reliability.
With its robust capabilities, SAS Data Management supports enterprise-wide data initiatives, including analytics, reporting, and compliance. It provides a scalable, secure platform for data scientists that can be deployed on-premises or in the cloud, catering to diverse business needs.
Portable is a modern ETL tool specifically designed for long-tail SaaS integrations. It offers no-code connectors for niche data sources, making it easy for businesses to integrate data into their analytics stack.
Portable excels in providing pre-built connectors and custom integrations on demand, enabling users to centralize their data efficiently.
It is ideal for organizations looking to manage sensitive data, from lesser-known tools alongside mainstream applications.
Dataddo is a versatile no-code ETL tool designed for seamless data integration and automation. It connects with a wide range of cloud applications, databases, and analytics tools, enabling businesses to centralize their data effortlessly.
Dataddo focuses on flexibility and ease of use, making it an ideal choice for organizations looking to build reliable data pipelines without technical complexity. It supports automated workflows and offers robust features for data synchronization and transformation.
Fivetran is a fully automated ETL tool that simplifies data integration by replicating data from various sources into your data warehouse. It supports a wide range of connectors, offering reliable and efficient pipelines with minimal maintenance.
Fivetran is known for its zero-configuration setup and automated schema management, making it an excellent choice for businesses seeking a hands-off approach to their data integration solutions.
The volumes of data collected by companies are getting bigger every day and will continue to grow. For now, working with local databases and batch loading is enough, but very soon, this will no longer satisfy business needs. Thus, the ability to scale ETL processes is convenient and especially relevant for advanced analytics.
When it comes to choosing an ETL tool, think about the specific needs of your business. If you are working locally and your data is predictable and comes from only a few sources, then a traditional ETL tool will be enough. But don't forget that more and more companies are moving to a cloud or hybrid architecture.
