Top 20 Best ETL Tools and Their (Pros and Cons)

Top 20 Best ETL Tools and Their (Pros and Cons). Modern organizations use data to predict trends, identify opportunities, and outdo competition. However, they most of them are faced with the challenge of processing data from the sources to the data warehouse and analytics tools. This is where Extract, Transform (ETL) tools come in handy. These tools extract data from the sources and transform it into models, before loading it into data warehouses. Basically, these tools connect to data sources and create a pipeline that enables data to flow in a unified system.

After all, ETL tools enable companies to consolidate data from multiple sources into a single location. This plays a crucial role in providing key business intelligence

Please read about Top 20 Best ETL Tools and Their (Pros and Cons).

Top 20 Best ETL Tools

1. SnapLogic

SnapLogic’s is an enterprise grade ETL Tool that loads data seamlessly into warehouses. Altogether, it uses the Intelligent Integration Platform (IIP), revolution ETL process for data integration. This approach eliminates the challenges associated with traditional ETL approaches, providing scalability, simplicity, and reliability whilst reducing time and costs. As a cloud native, multi tenant platform, it offers a versatile solution for public cloud platforms. With hybrid data processing engine, it delivers unmatched scalability and parallel processing power. 

With over 600 pre-built connectors (Snaps), they help users to create data pipelines easily to access data. SnapLogic’s AI powered integration assistant, SnapLogic Iris, further streamlines the pipeline building process in a low code/no code environment.

Pros of SnapLogic

  • 100% REST based architecture enabling users to connect to various sources and create ETL pipelines.
  • Handles a range of integration scenarios, such as one to one, one to many, many to one, or many to many.
  • Integrated API development and management (APIM) platform to enable data sharing and collaboration.

Cons of SnapLogic

  • Poor user interface.
  • Limited documentation especially on error handling.

2. IBM InfoSphere DataStage

IBM InfoSphere DataStage is another of our Top 20 Best ETL Tools. A data integration platform with powerful ETL capabilities. What is more, it ingests data from multiple sources such as relational databases, indexed files, and sequential files their data warehouses. DataStage equips businesses with the tools they need to improve their data integration, data quality, and data governance efforts, ultimately leading to better data driven decision making.

Well, it is suitable for large organizations that handle large volumes of data with high performance and scalability. The platform’s parallel processing capabilities allow it to keep up with the ever growing demands of modern data driven environments. Extensive library of pre built transformations and connectors also simplifies the ETL process. 

Pros of IBM InfoSphere

  • Compatible with a wide variety of data sources and formats ensures smooth integration with multiple applications and systems.
  • Scalable parallel processing approach.
  • Synchronize and refresh data as much as you want.
  • Multiple ways of authenticating users.

Cons of IBM InfoSphere

  • Not fully compatible with Oracle.
  • Requires you to understand algorithms.

3. Oracle Data Integrator

Oracle Data Integrator (ODI) is a user friendly ETL tool that provides all styles of data integration i.e service based, event based, and data based. As part of the Oracle Fusion Middleware suite, ODI helps businesses bring their data together seamlessly, empowering them to make well informed decisions. Another key point, is that it is designed to work with a wide array of data sources and formats.

Besides, ODI uses a smart, declarative design approach along with Knowledge Modules (KMs) to automate code generation. Certainly, this approach saves time and cuts development and maintenance tasks. On top of that, its ELT architecture makes the most of the target systems’ processing power, which leads to better performance and less strain on resources.

Pros of Oracle Data Integrator

  • Intuitive interface.
  • Wide range of pre built components, and support for both batch and real time data integration.
  • Integrates seamlessly with Oracle GoldenGate to achieve data replication to keep databases and data warehouses synchronized.
  • Prebuilt connectors for big data platforms such as Spark Streaming, HadoopKafka, Hive, HBase, Sqoop.
  • Has a declarative design with data mapping rules to accelerate development and improve productivity.

Cons of Oracle Data Integrator

  • Audit module does not easily debug failed instances.
  • Relatively expensive.

4. Fivetran

Following on our list of Top 20 Best ETL Tools is Fivetran. All in all, a versatile, cloud based, automated ETL tool designed to simplify data management and consolidation. With 300 pre built data connectors, Fivetran enables users to easily integrate data from various sources. Simply adapts to API and schema changes to ensure data consistency and integrity, while providing a low code solution through pre built data models. This approach allows users to quickly generate reports and respond to queries without expending significant engineering resources.

Concurrently, Fivetran keeps adding connectors that are not available, while also allowing users to create their own custom connectors. This flexibility makes it a handy ETL tool that does not require writing custom SQL queries.

Pros of Fivetran

  • Provides near real time data replication.
  • 24/7 customer Support Specialists.
  • Easy to read documentation.
  • Easy to configure and maintain existing pipelines.

Cons of Fivetran

  • Complex pricing structure.
  • Limits you if you don’t know how to code your own connectors and models.

5. Microsoft SQL Server Integration Services (SSIS)

Microsoft SQL Server Integration Services (SSIS) is a data integration service that extracts and transforms data from multiple services and loads it into your preferred warehouse. It has set of features and graphical tools suitable for building packages. SSIS has control flow engine that orchestrates tasks and manages the execution of tasks. Create workflows with loops, branching, and conditional logic. This ensures the right sequence of tasks in your data integration processes.

Besides, SSIS also offers tools for deploying, managing, and monitoring packages. These tools include the Catalog, which stores package metadata and execution history. It also integrates with SQL Server Management Studio (SSMS) and Azure Data Factory to manage and monitor your SSIS packages from a central console.

Further, it is highly extensible, allowing you to create custom scripts in C# or .NET. Consequently, allows you to integrate these scripts and components into your data workflows. As can be seen, it uses SSIS for data archiving and indexing.

Pros of SSIS

  • Enables users to handle errors within a dataflow.
  • Integrates seamless with other Microsoft products to increase productivity.
  • Loads large amounts of data from Excel to SQL server database without the need for extensive programming.

Cons of SSIS

  • Only supported in Microsoft Windows.
  • Limited integration other third party tools.

6. Informatica PowerCenter

Informatica PowerCenter is a widely used, enterprise grade ETL tool that offers comprehensive data integration and management solutions. PowerCenter’s primary strength lies in its ability to handle large volumes of data and complex transformations, making it suitable for organizations with massive and intricate data operations.

Equally, with PowerCenter it has a metadata driven approach that allows for better data governance and lineage tracking. In addition, it has reusable components and templates that facilitate faster development and deployment of ETL processes. PowerCenter also provides advanced data profiling, data quality, and data masking features. All these features ensure the integrity and security of sensitive information.

Pros of Informatica PowerCenter

  • Supports a multi user development environment.
  • Has enough connectors to cover all possible data sources.
  • Flow visualizations that help users identify source of data.
  • Provides code reusability with shared connections.

Cons of Informatica PowerCenter

  • Requires some training.
  • Not available for MacOS.


Another choice of Top 20 Best ETL Tools and Their (Pros and Cons) is All things considered, a unified stack for modern data teams. Moreover it is cloud based data integration platform that enables you to create simple, visualized data pipelines for your data warehouse. What it does, it combines all your data sources to centralize metrics and sales tools like CRM, automation, and customer support systems. Similarly, the platform is elastic and scalable and works with structured and unstructured data. 

The platform easily integrates with sources like NoSQL databases, SQL data sources, and cloud storage services. It also works with relational databases such as Amazon RDS, Microsoft SQL Server, and Oracle. is the no-code data pipeline platform for your entire data journey.

Pros of

  • Complete set of ETL tools and connectors for accessible building and managing of clean and secure data pipelines.
  • The powerful drag and drop interface enables you to prepare and transform your data easily.
  • Has a write REST API code automation feature
  • Data observability and alerts in real time. 
  • Future proofs your data journey as you scale your database.

Cons of

  • Lacks documentation for advanced capabilities.
  • Poor salesforce integrator connector needs improvement.

8. iCEDQ

iCEDQ is a data testing and observability platform designed to automate your ETL process. Designed to help organizations improve data quality, accuracy, and integrity throughout their pipelines. Test and validate data in ETL processes, data migrations, warehousing, and reporting. Especially, it also identifies and addresses data issues proactively, enabling organizations maintain reliable and accurate data.

Evidently, it has comprehensive set of data testing capabilities like data validation, reconciliation, and profiling. In turn, that allows users to verify the accuracy, consistency, and completeness of their data and identify potential issues early in the data lifecycle. Users create custom data validation rules using a visual interface or scripting. Eventually, this makes it easy to enforce specific data quality standards.

Pros of iCEDQ

  • Designed for high performance data warehouse testing.
  • Provides end to end data pipeline testing.
  • Identifies data integration errors without custom code.
  • Compares data in memory based on unique columns in the database.
  • Easily switch between data connections.

Cons of iCEDQ

  • Often generates false positives.

9. AWS Glue

AWS Glue is a managed ETL cloud service used to prepare data for analytics and machine learning and application development. It provides a wide range of data integration capabilities, including visual and code based interfaces. 

A fully managed service, which means you don’t have to provision the underlying infrastructure. Provides built in tools and templates to create, schedule, and manage ETL jobs. These jobs use Apache Spark or Python shell to process and transform data. Therefore, you focus on your data processing logic rather than managing infrastructure. 

Evidently, AWS Glue Crawlers connect to the ETL service to the data source. Once connected, the data is ingested into the Data Catalog. Moreover, Glue also provides development endpoints to help you develop and test your ETL scripts in a notebook environment, such as Jupyter.

Pros of AWS Glue

  • Runs in a serverless environment.
  • Automatic schema discovery that crawls your data sources to identify formats.
  • Automatically generates code in either Python or Scala.
  • Has a fault tolerance feature to help you retrieve failed jobs.

Cons of AWS Glue

  • Limited compatibility with data sources outside AWS.
  • Not suitable for real time ETL jobs as all data is staged on S3 first.
  • Requires a deep understanding of Apache Spark.

10. CData Sync

CData Sync is an ETL solution that provides pipelines for continuous data flow from data sources to warehouses. It provides 250+ connectors that allow you to work with any source. Supports data sources such relational and NoSQL databases, cloud and on premises applications, and file formats.

Hence, it offers incremental data replication capabilities to ensure consistent, reliable, and up to date reporting. This enables it to identify and sync only the changed data between the source and the destination. This approach reduces data transfer volumes and improves the replication process. Besides, CData Sync offers data transformation features that allow you to modify, cleanse, and enrich the data as it is moved between systems.

Balanced against, CData Sync also supports cloud migration thanks to location agonistic data pipelines. It provides a secure way of building pipelines for on premise to cloud locations.

Pros of CData Sync

  • Simple and easy to use.
  • Suitable if you want to build a powerful data warehouse.
  • Easy to sync between multiple connections.
  • Has a highly flexible configuration engine.

Cons of CData Sync

  • Relatively expensive especially for small companies and startups.
  • Lacks sufficient documentation.
  • Lacks advanced security features.

11. Stitch

Stitch ETL provides enterprise level features to enable organizations handle complex data integration. Holds dedicated infrastructure, data residency options, and custom SLAs. All these features ensure enterprises perform ETL process with high performance. With its data replication through automatically scaling this tool helps users optimize their data pipelines and achieve faster data loading times.

Following, it also provides an extensible framework for developers to build custom integrations. 

Pros of Stitch ETL

  • Designed to enable organizations comply with regulatory standards such as GDPR, HIPAA, and SOC 2.
  • Provides Extration Logs and Loading Reports to help monitor and review replication progress.
  • Provides service level agreements to guarantee users uptime and support.
  • Has a reliable, comprehensive documentation.
  • Developers use either the API or JavaScript client to extract data and load into warehouses.

Cons of Stitch ETL

  • Error messages are often complex and make it difficult to identify the sources.
  • Difficult to replicate document stores like MongoDB.

12. Azure Data Factory

Azure Data Factory is a cloud ETL tool designed to improve data integration and management processes. Generally, it offers serverless pipelines for data orchestration and movement. One of the main features is the Mapping Data Flow which offers a user friendly, visual interface for designing data transformations without the need for coding. 

Another notable feature is the Integration Runtime (IR), which facilitates secure data movement and processing within specific network environments. Users choose from three IR types – Azure, Self-hosted, and Azure-SSIS  to best meet their data integration requirements. Moreover, Azure Data Factory includes support for triggers, enabling users to schedule and automate pipelines based on time, data events, or external factors. 

Finally, Azure Data Factory supports CI/CD practices through Azure DevOps, Git repositories, and ARM templates. This facilitates agile development, version control, and efficient data pipeline deployment.

Pros of Azure Data Factory

  • Extensive monitoring and management features, such as integration with Azure Monitor.
  • Wide array of APIs and SDKs for programmatic interaction.
  • 90+ built in connectors to ingest data from hybrid cloud, SaaS, on premise servers, and other databases.
  • Automated ETL capabilities to increase efficiency and reduce the need for maintaining pipelines.
  • Fully managed and codeless to hence suitable for non-programmers.
  • Rehost and extend SQL Server Integration Services (SSIS) and build pipelines faster.

Cons of Azure Data Factory

  • Requires proper knowledge of Azure cloud.
  • Costs escalate out of control if not well monitored.

13. Qlik Replicate

Qlik Replicate is a cost effective ETL solution that enables organizations to achieve real time data integration. By leveraging Qlik Replicate, organizations consolidate data from disparate systems, ensure data consistency, and accelerate data migration projects. Delivers high performance replication using Change Data Capture (CDC) technology. This technology enables low latency and low impact data replication by identifying and capturing only the changes made to the source data. 

Henceforth, it allows for data extraction and transformation on the fly. This ensures that businesses have access to the most up-to-date and accurate information needed to make critical decisions. Equally important, it supports a wide array of data sources and target systems, including relational databases (e.g., Oracle, SQL Server, MySQL). It also supports data warehouses (e.g., Snowflake, Teradata), and big data platforms (e.g., Hadoop, Apache Kafka).

Pros of Qlik

  • Updates and validates data in real time, enabling businesses to react to changes more rapidly.
  • Identifies and fixes data issues.
  • Move data across enterprise or hybrid environments with high throughput and low latency.
  • Secures data with AES-256 encryption.

Cons of Qlik

  • Not easy to troubleshoot.
  • Limited documentation.
  • Lack of coding minimizes customization options.

14. Google Cloud Dataflow

Google Cloud Dataflow is a unified data processing and stream service designed for real time data processing. Identically, it is build and manages scalable data pipelines that integrate large volumes of data. Uses Apache Beam which means you write your data pipelines once and then run them on different processing engines like Apache Flink or Apache Spark.

Ingest data in any batch mode or from any database. Handles multiple data structures in the PCollections format. Also, it has a library known as PTransforms that allows repeated tasks using basic templates. The auto scaling feature maximizes resource allocation. 

Pros of Google Cloud Dataflow

  • Integrates seamlessly with other Google Cloud services like BigQuery, Pub/Sub, and Cloud Storage to enable data movement.
  • Serverless architecture,
  • Integrates with Google Cloud’s Stackdriver Monitoring and Logging to help users diagnose and troubleshoot issues.
  • Provides streaming with low data latency.
  • Powered by real time AI capabilities to with near human intelligence.

Cons of Google Cloud Dataflow

  • Few connector options.

15. Matillion

Matillion is a cloud based ETL that allows automation and acceleration of data integration. It has lots of connectors that allow you to integrate data from any system, app or cloud platform. Likewise, it allows a single control pane where you simplify the pipeline management. Nevertheless, Matillion also enables you to cleanse and enrich data and build data pipelines in minutes. 

Pros of Matillion

  • Native support for all major cloud data platforms.
  • Enables users to achieve optimum performance with push down integration.
  • Independent scaling of storage and compute services allows for optimum resource utilization.
  • Delivers fast ETL by running multiple processes concurrently.
  • The no code GUI enables you to build sophisticated data pipelines.

Cons of Matillion

  • Limited integration for large applications such as Salesforce.
  • Difficult to debug.
  • Complex documentation.

16. AWS Data Pipeline

AWS Data Pipeline is a managed ETL service from Amazon that moves data between AWS storage and computing services. Offers prebuilt activities and integrations to perform data processing tasks such as running Amazon EMR jobs, executing SQL queries on RDS, and more. This tool supports a wide range of AWS data sources and destinations, including Amazon S3, Amazon DynamoDB, Amazon Redshift

Nonetheless, AWS Pipeline gives huge flexibility and customization. Users define custom data processing logic using scripts, applications, or executable files. So organizations implement custom data processing workflows and even build reusable pipeline templates for common data processing patterns. A

Designed to handle failures and errors gracefully, ensuring reliable data processing. It automatically retries failed tasks, creates backup copies of data, and sends notifications in case of failures or errors.

Pros of AWS Pipeline

  • Secures data through encryption and fine grained access control through AWS IAM.
  • Complies with various regulatory requirements such as SOC2 and HIPAA. 
  • Offers pre built logging and monitoring features
  • Drag and drop console to create pipelines quickly.
  • Use for free under the AWS Free Usage.

Cons of AWS Pipeline

  • Limited integration with third party apps.
  • Very complex to set up for inexperienced users.

17. Skyvia

Skyvia ETL is a powerful cloud based data integration solution that offers a comprehensive suite of tools for ETL processes. Overall, users efficiently connect and manage data from a wide array of sources, including databases, cloud applications, and flat files. The platform provides seamless integration with popular data sources like Salesforce, QuickBooks, MySQL, and SQL Server. Ideal choice for businesses of all sizes to streamline their data workflows.

One of the standout features of Skyvia ETL is its robust import functionality. In addition, users easily import from cloud, databases, and CSV files. Also streamlines the export of data to warehouses and analytics solutions. Powerful data transformations and mapping capabilities which simplify complex data migration tasks.  Particularly, it is Skyvia’s import feature that provides scheduling options, allowing users to set up recurring data transfers. 

Pros of Skyvia

  • Preserves data relations during import and migration.
  • Performs synchronization of changes between data sources,
  • Configure your import operations in a few clicks.
  • Query and manage data from browser via Query Builder or SQL.

Cons of Skyvia

  • The synchronization process is time consuming.
  • No provide real time support.

18. Dataddo

Dataddo is a powerful ETL solution that delivers versatile data integration, enabling businesses to ingest data from various sources into warehouses. Simultaneously, it connects and unifies data from various APIs, databases, and cloud services

The main advantage of Dataddo is its ability to handle data transformations on the fly, allowing businesses to aggregate, filter, and restructure data as it is being processed. In effect this ensures that the data is ready for immediate analysis and visualization in your data warehouse. Furthermore, the platform offers data synchronization, which ensures that your data is always up to date. 

Pros of Dataddo

  • A no code platform suitable for non-technical users.
  • Flexible regardless of the type of data warehouse or data lake you are using.
  • Performs automatic data quality checks to detect anomalies in your pipelines.
  • Compliant with all major security standards.

Cons of Dataddo

  • Limited customization. Unsuitable for companies that need more granular control.
  • No support for custom data sources.

19. Talend

Talend is an open ETL tool for data integration. Combines best in class data integration capabilities to give users enhanced insights and control over data. Specifically, it provides connectors for RDBMS, Packaged apps, and SaaS tools. Besides, it ensures data is usable for artificial intelligence, machine learning, and analytics.

Pros of Talend

  • Based on Eclipse IDE which makes it suitable for developers.
  • Monitors real time data flow.
  • Intuitive user interface.

Cons of Talend

  • Requires knowledge of Java for complex developers
  • Often crashes when transforming large datasets.

20.SAP Datasphere

Last but not least on Top 20 Best ETL Tools and Their (Pros and Cons) is SAP Datasphere. Similarly, an ETL tool that enables data scientists to deliver seamless and scalable access to mission critical business data. Build a business data fabric on the SAP Business Technology Platform for a unified experience for data integration, semantic modelling, cataloguing, federation, warehousing, and visualization.

Pros of SAP Datasphere

  • Provides access to authoritative data with semantical definitions and associations from SAP applications. 
  • Harmonizes heterogeneous data into a semantic business model of a diverse data landscape. 
  • Simplifies the data landscape to provide access to data across hybrid and cloud environments .
  • Easily visualize data without coding.

Cons of SAP Datasphere

  • The pricing is too high for start-ups and SMEs.
  • The tool lacks a mobile application like that of the Google Cloud Console.

Thank you for reading Top 20 Best ETL Tools and Their (Pros and Cons). We shall conclude the article.

Top 20 Best ETL Tools and Their (Pros and Cons) Conclusion

Concluding, as data becomes more important for businesses, it is imperative to have a reliable ETL solution. Finally, choosing the right ETL tool is helps your organization stay competitive and data driven. Each ETL tool reviewed offers its own unique set of features, capabilities, and pricing models, catering to a variety of needs and preferences. Some tools offer more user friendliness and ease of integration, while others offer powerful customization options and scalability. Therefore, it is crucial to carefully consider your specific requirements, budget, and technical expertise when selecting an ETL tool.

Avatar for Dennis Muvaa
Dennis Muvaa

Dennis is an expert content writer and SEO strategist in cloud technologies such as AWS, Azure, and GCP. He's also experienced in cybersecurity, big data, and AI.

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