Best ETL Tools in 2023 
Data & Analytics
Best ETL Tools in 2023 
Best ETL Tools in 2023 
Data & Analytics

Best ETL Tools in 2023 

According to big data statistics, data creation, capturing, copying, and consumption increased from 1.2 trillion gigabytes to almost 60 trillion gigabytes (about 5000%) between 2010 and 2020. 

For organizations, this data includes a wide range of information covering customers, employees, products, and services, which must be standardized and shared among various teams and systems. Partners and vendors may even have access to this data. 

As the volume of data uses continues to grow, ETL tools (Extract, Transform, Load) have become an increasingly popular method for organizations looking to keep up with the demand for more timely and accurate insights.  

In this article, we’ve compiled a list of the best ETL tools for 2022 so that you can choose the one that best suits your business needs. 

What Are ETL Tools? 

ETL is the process of extracting data from multiple sources, transforming it into a new format, and loading it into a data warehouse or other storage. Data can be extracted from different types of databases, files, and applications. 

An ETL tool helps to automate this process via three core functions:  

  • Extraction of data from underlying data sources.  
  • Data transformation to meet the criteria for enterprise repositories like data warehouses.  
  • Data loading into target destination. 

These tools help to transform, cleanse and consolidate data from multiple sources, but can also be used in other scenarios where complex data transformation is required. 

Types of ETL Tools 

There are a few different types of ETL tools available on the market, each with its own set of features and benefits. Here is a brief overview of some of the most popular types of ETL tools: 

Open Source ETL Tools 

These tools are typically community-developed and supported, free to download and use, and offer a wide range of features. There are several open-source ETL tools available, such as Talend, Pentaho, and Jaspersoft ETL.  

Apache Airflow is also worthy of mention. While not an ETL tool per se, Apache Airflow can assist you in automating the extract, transform, and load (ETL) process. This open source platform enables the development, scheduling, and monitoring of batch-oriented workflows in ETL pipelines using Directed Acyclic Graphs (DAGs). 

One of the main benefits of using an open-source ETL tool is that you have the freedom to customize the tool to suit your specific needs. 

Enterprise Software ETL Tools 

Enterprise software ETL tools are commercial products that are typically developed and supported by a vendor. They are usually more feature-rich and comprehensive than open-source ETL tools, but they can also be more expensive. One of the most popular enterprise ETL tools is Informatica PowerCenter.  

Cloud-Based ETL Tools 

Cloud ETL tools are tools that are hosted in the cloud. They are typically pay-as-you-go services, so you only pay for the resources you use. One of the most popular cloud-based ETL tools is Amazon Glue.  

Custom ETL Tools 

Custom ETL tools are designed to meet the specific needs of a business. They are often more complex and require more technical expertise to use. However, they can be customized to exactly match a business’s needs, which can make them well worth the investment. 

Best ETL Tools in the Market 

Here are some of the popular ETL tools you can use to make a difference in your organization. 

Google Cloud Dataflow 

Google Dataflow is a serverless ETL solution that allows pipelines to be executed within the Google Cloud Platform environment. It transforms and enhances data in both batch (historical) and stream (real-time) modes. 

Apache Beam is at the heart of Dataflow. An open-source pipeline definition tool for batch and streaming data, Apache Beam provides all the essential components for defining pipelines, executing them locally, and deploying on Cloud Dataflow. 

Amazon Kinesis, Apache Storm, Apache Spark, and Facebook Flux are among the software frameworks and services supported by Google Cloud Dataflow. 

If you are looking for a tool to complement dataflow, then you should look at Cloud Data Fusion framework by Google. Based on the open source pipeline development tool CDAP, data fusion provides a simple drag and drop user interface to design data pipelines. Google cloud data fusion boasts additional features like metadata management and data lineage. 

AWS Glue 

AWS Glue is a serverless ETL solution that simplifies the discovery, preparation, movement, and integration of data from many sources. It has applications in analytics, machine learning, and app development. 

AWS Glue facilitates your ETL jobs by leveraging other AWS services. It invokes API operations to transform your data, generate runtime logs, save your job logic, and generate notifications to assist you in monitoring your job runs. 

According to PeerSpot, AWS Glue is the second-best option for cloud data integration technologies. 

Azure Data Factory 

Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows to orchestrate and automate data movement and data transformation.  

It supports a wide range of data sources, including on-premises sources such as SQL Server and Oracle, as well as cloud-based sources such as Azure SQL Database and Azure Blob storage. It also includes a built-in visual monitor that makes it easy to create and monitor ETL pipelines. 

Azure Data Factory was ranked #1 for top Data Integration Tools and #2 for top Cloud Data Warehouse Tools according to PeerSpot. 


Stitch is a cloud-based ETL tool that offers a simple, powerful, and easy-to-use web interface. It includes a data warehouse integrator that allows you to quickly and easily connect to your data sources and a transformation engine that lets you easily transform and manipulate your data in a way that is useful and compatible with your destination.  

Stitch also offers a variety of features, including support for SQL and MongoDB, transparent data pipelines, and a flexible pricing model.  

The G2 community has given Stitch generally positive reviews

Oracle Data Integrator 

Oracle Data Integrator is a powerful, enterprise-grade ETL tool that offers a wide range of features and capabilities. It includes a drag-and-drop interface that makes it easy to create and edit data transformations, and a wide range of connectors to connect to data sources.  

Oracle Data Integrator is one of the best ETL tools for big data. It also offers support for data masking (for data residing in flat files, XML files, or RDBMS). Oracle Data Integrator also has an active integration platform that supports three types of data integration: data-based, event-based, and service-based. 

Oracle Data Integrator (ODI) has an overall score of 8.2 out of 10 and is the fourth-ranked product among Data Integration Tools on PeerSpot. 

IBM DataStage 

IBM DataStage is a high-performance ETL tool that helps to move data from one source to another. It can also be used for data integration, data warehousing, and business intelligence.  

It has a very powerful GUI, which allows users to design their job steps that move data from source systems to target systems and easily manage the entire process. The tool is available in two versions: on-premise and cloud. 

There are about 13,087 companies using Datastage including the Bank of America. 

SAS Data Management 

SAS Data Management is another popular ETL tool that can be used for data integration between multiple sources such as databases, spreadsheets, and web services. It allows users to create and modify data management processes using a visual, end-to-end event designer.  

This tool also provides several user-friendly features including drag-and-drop functionality and the ability to practically link any source or target data repository and to distribute data integration tasks across any ecosystem. 

On PeerSpot’s list of the top Data Integration Tools, SAS Data Management is placed as the #19 solution

Talend Open Studio 

Talend Open Studio is a free ETL tool (open-source) that helps users quickly and easily convert, combine, and update data in various locations. It offers a graphical interface that makes data transformation and preparation tasks easy to understand and carry out and is one of the free ETL tools that allows big data integration, data quality, and master data management. 

For the seventh year running, Talend has been recognized by Gartner as a Leader in the 2022 Magic Quadrant for Data Integration Tools


Singer is a free and open-source data extraction tool that enables users to extract data from a variety of sources called taps, including relational databases, MySQL, Amazon S3, and Facebook.  

Singer provides a more straightforward solution to unifying your data operations, eliminating the need to write your software to handle data sources. 


Hadoop is an open-source framework that is used for data processing and storage in big data applications. Not many people believe it belongs on an ETL tool list, but it can help with the ETL process. Hadoop provides tools for extracting data from source systems like log files, machine data, or online databases and loading it into Hadoop on time.  

Studies show that before the end of 2022, 8% of organizations will have deployed at least one Hadoop initiative. 


Using Dataddo, you can integrate and manage cloud applications, dashboarding tools, data warehouses, and data lakes without needing to write code.  

Dataddo comes in three variants:  

  • Data to Dashboards, which enables users to send data from online sources straight to dashboarding apps like Tableau, Power BI, and Google Data Studio. 
  • Data anywhere, which allows users to transfer data from one location to another, including from applications to warehouses, from warehouses back into apps, and from one warehouse to another. 
  • Headless Data Integration, which allows enterprises to create their data products via the Dataddo API. 

Dataddo experienced a 20% increase in 2021 and currently supports over 17,000 businesses and people, including Twitter and Uber Eats. 

Informatica PowerCenter 

Informatica PowerCenter is an ETL solution used to extract, transform, and load data from several heterogeneous sources. 

It delivers a rich range of functionality such as data operations at the row level, data integration from various structured, semi-structured, or unstructured platforms, and data operation scheduling. It also includes metadata, which preserves information about the data operations. 

One of the most popular ETL tools in the world, Informatica PowerCenter is ranked #2 by PeerSpot in both the top data integration tools and the top data visualization tools categories. 


Fivetran delivers automated data integration and ready-to-use connections that automatically detect when schemas and APIs change, delivering consistent, dependable data access.  

Fivetran optimizes the quality of data-driven insights by continually syncing data from various sources to any destination so that people can work with the most up-to-date information available. Fivetran supports in-warehouse transformations and provides source-specific analytics templates to expedite analytics. 

Gartner recognizes Fivetran as a Niche Player in its Magic Quadrant for Data Integration. 

Pentaho Data Integration 

Pentaho Data Integration (PDI) provides robust Extraction, Transformation, and Loading (ETL) functionality using a revolutionary, metadata-driven methodology. 

PDI incorporates Kitchen, a task and transformation runner, and Spoon, a graphical user interface for designing such jobs and transformations. 

This intuitive, graphical, drag-and-drop design environment is easy to use and requires less time to master. Pentaho Data Integration is increasingly being chosen by enterprises over conventional, bespoke ETL or data integration products. 

According to Enlyft, there are 13,030 brands using PDI including Red Hat and California State University. 

Use Cases For Top ETL Tools 

As we have already established, in the world of data, Extract, Transform, Load (ETL) tools play a vital role. However, because no two solutions are the same, it is important that you fully understand your business needs, goals, and priorities in other to identify the one that works for you.  

Considering the ETL tool comparison above, this next section covers 8 top solutions and the kind of user groups that will be interested in each one.  

  • IBM DataStage: Enterprise organizations with 1,000 workers or more, as well as businesses in the financial services sector. This platform is especially useful for businesses that deal with large data sets and have several data rules in place. 
  • Talend: Companies of any size that prefer an open-source solution. It is also perfect for companies looking for a simple-to-use tool, thanks to its user-friendly GUI and built-in integration. 
  • Azure Data Factory: Enterprises with more than 1,000 workers are the most likely to adopt Azure ETL tools. These businesses naturally handle a lot of data and employ huge employees. It is ideal for organizations looking for a solution to load data from several ERP systems into Azure Synapse for reporting. 
  • Stitch: Organizations that favor open-source software that enables simple integration with a variety of sources. It is also ideal for businesses that want a straightforward ELT approach and don’t need sophisticated transformations. 
  • AWS Glue: For organizations that predominantly use ETL and prefer to execute their processes on a serverless Apache Spark-based infrastructure 
  • Informatica PowerCenter: For organizations looking to process semi-structured and structured files for data warehouse loading and reporting. For the most part, these are usually big businesses with sizable expenditures and strict performance requirements. However, it works for small companies too. 
  • Oracle Data Integrator: Companies that specialize in data warehousing, data migration, big data integration, master data management, and application integration. Perfect for businesses searching for a solution that effortlessly connects to several databases such as MySql, SQL Server, and others. 
  • Fivetran: Any organization that needs dependable and timely data through a secure pipeline. Companies who want to supplement their existing contemporary data stacks and ETL procedures. Ideal for enterprises wishing to replicate existing apps, workflows, and databases into a cloud data warehouse in a seamless manner. 

Concluding Remarks 

There you have it. The best ETL tools for 2022.  

These solutions are available in several flavors to satisfy the demands of both large and small businesses but the best one for you will depend on factors unique to your organization including data needs, company size, number of features, and budget.  

If you are looking for a solution that is tailor-made for your company alone, then you should consider investing in a custom tool. This is where we can help. 

Symphony Solutions provide custom enterprise software development. With more than 10 years of serving growth-oriented clients, we have the skills, expertise, and resources to deliver the solution you need. 

To have an idea of what we can do, check out this case study: Enabling Business to Make the Right Decisions on Time by Building a Centralized Data Management Solution.  

Get in touch today for a no-obligation quote. We would be happy to help you find the right solution for your needs. 


Based on market share details, Informatica PowerCenter is the best ETL tool, as well as the most used. It takes up 19.20% of the ETL tools market share and is used by more than 8400 companies. 

ETL tools in SQL help users extract data from a source, transform it into a format that is compatible with another system, and load it into that system. 

Although Python is not an ETL tool, it is a common programming language used to build ETL pipelines. You can build more effective ETL pipelines with Python frameworks. 

In Excel, there is a data analysis tool called Get and Transform. This tool can perform ETL functions, such as cleaning and sorting raw data from a range of input sources, such as CSVs and text files. It is common for data analysts to carry out basic ETL operations using this advanced Excel feature.