Organizations today have access to an immense volume of data. To put it into perspective, in 2022, an estimated 97 zettabytes of data were generated globally—that’s a staggering 97 trillion gigabytes!

However, this data will remain untapped without the appropriate means to extract, transform, and load it into a storage system for decision-making. Consequently, ETL tools have become indispensable for forward-thinking organizations looking to integrate data without relying heavily on IT.

What are ETL tools?

ETL tools are software solutions that allow businesses to extract data from disparate sources, transform it, and load it into target systems, such as a data lake or data warehouse, for reporting and analytics.

These tools help leverage large amounts of data from multiple sources. Modern ETL solutions, like Astera, support real-time or batch processing, offer scalable architectures, and integrate with other technologies such as business intelligence (BI) and data visualization tools.

The list of best ETL tools in 2024:

1. Astera
2. Integrate
3. Fivetran
4. Talend
5. Hevo Data
6. Skyvia
7. SAS Data Management
8. Pentaho
9. Stitch
10. Blendo
11. Airbyte
12. Azure Data Factory
13. Oracle Data Integrator
14. Apache Airflow
15. Portable.io

How Can an ETL Tool Help Data Teams?

Traditionally, businesses set up ETL pipelines through manual coding, which is inefficient and time-consuming. The primary problem with the programming stack is that data is manipulated by the element instead of columns and rows, making it difficult to integrate heterogeneous sources.

Moreover, adding or changing data pipelines requires building on top of previous libraries and complex code integration. Therefore, modern businesses have started using automated ETL tools that can handle intricate ETL processes more efficiently.

ETL tools simplify the ETL process by abstracting these complexities and enabling non-technical users to handle data transformations and workflows. This abstraction streamlines development, maintenance, and scalability, making ETL processes more accessible and efficient for a wider range of users within an organization.

Here are some reasons why you should opt for an ETL tool:

ETL Tools Build Data Pipelines Faster

Like other data integration tools, ETL tools use automation to integrate data and build data pipelines faster. They come equipped with pre-built connectors for diverse data sources and destinations, minimizing the need for custom coding and allowing for faster implementation. They also offer a visual interface for designing and managing data pipelines more seamlessly, so users with minimal to no coding experience can easily build and maintain data pipelines.

ETL Tools are Future-Proof

Modern ETL tools are designed to be adaptable and flexible to handle constantly changing data requirements and technologies. Most ETL tool vendors constantly update functionalities and add connectors in response to new technologies and best practices.

ETL Tool can Handle Complex Data Easily

Handling complex and unstructured raw data is a difficult task. ETL tools have evolved to address this challenge by incorporating features and capabilities to handle data in various formats and structures. Moreover, many ETL solutions allow users to write custom transformations to ingest, cleanse, and manipulate complex data.

ETL Tools Reduce Error Probability

ETL Tools significantly reduce the risk of errors in data pipelines, mainly through automation. Eliminating manual tasks also eliminate the risk of human errors. Moreover, many ETL tools come with data validation controls to ensure that data passes the specified criteria before reaching a target destination. The visual interface and workflow also help reduce the probability of errors.

Types of ETL Tools

The growing demand for effective data management and the increasing volume, variety, and velocity of data has led to the development of different classes of tools, including:

Open Source ETL Tools

Open-source ETL tools are free to use. You can easily access their source code and extend its functionality to meet your data requirements. While open-source ETL tools are flexible, they lack the user-friendly UI that most commercial tools feature. Moreover, they offer limited functionality and it’s highly likely that a given open-source solution will be incompatible with your existing data pipelines.

Custom ETL Tools

Many businesses design their ETL solutions in-house using data pipelines and programming languages such as Python and SQL. While they enable greater customization to meet specific data requirements, these tools are time-consuming to build and complex to maintain. An in-house ETL solution is feasible for businesses dealing with limited amount of data and simple data pipelines.

Cloud-based ETL Tools

Cloud-based ETL tools allow you to manage data from various cloud-based applications. These solutions are deployed on the cloud to process large volumes of data without investing in additional infrastructure.

Enterprise ETL tools

Enterprise ETL software are specialized solutions for large organizations to perform ETL processes efficiently. You can ingest data from disparate sources into a centralized data repository for reporting and analytics. These solutions have advanced capabilities to perform complex data transformations and handle data processing at scale.

Many vendors charge an annual license fee or follow a pay-as-you-go model. Top providers offer extensive training and resources in addition to the ETL functionality. Enterprise ETL tools are easy to use, even for business users, as they feature no-code interfaces powered by drag-and-drop and point-and-click functionalities.

The Top 15 ETL Tools in 2024

Today, several ETL tools are available in the market, differing in their offerings and the types of use cases supported.

1. Astera
2. Integrate
3. Fivetran
4. Talend
5. Hevo Data
6. Skyvia
7. SAS Data Management
8. Pentaho
9. Stitch
10. Blendo
11. Airbyte
12. Azure Data Factory
13. Oracle Data Integrator
14. Apache Airflow
15. Portable.io

Astera

Astera is a unified, no-code platform for enterprises that want to simplify their ETL and ELT processes. Equipped with an intuitive, easy-to-use interface, it allows you to create automated data pipelines that integrate and process data from disparate sources. Beyond ETL, Astera provides an end-to-end data ecosystem for data extraction, integration, electronic data interchange (EDI), API management, and data warehousing.

Key features of Astera:

• Powerful ETL Engine: Built on a robust parallel-processing engine, Astera effortlessly handles large volumes of datasets, ensuring smooth and efficient ETL operations with speed.
• Automation and Orchestration: Astera streamlines workflows through job scheduling features, allowing you to set up processes once and automate execution.
• Intuitive, No-Code Interface: The tool prioritizes user-friendliness and offers a drag-and-drop interface that empowers both business and technical users to handle complex ETL tasks with ease.
• Extensive Connector Library: Astera supports a wide array of connectors for both on-premises and cloud-based sources and destinations, including databases, data warehouses, and data lakes. Additionally, you can easily connect to other sources or destinations through pre-built API connectors.
• AI-Powered Data Extraction: The solution offers intelligent document processing. The AI-powered extraction allows you to effortlessly capture data from semi-structured and unstructured documents.
• Data Transformation Capabilities: Astera offers a range of built-in advanced transformations and functions, such as Tree Join, Normalization, sort, filter, distinct, etc which simplifies data manipulation. You can easily drag and drop the required transformations and map them within your data pipelines.
• Extensive Connector Library: Astera supports a wide array of connectors for both on-premises and cloud-based sources and destinations, including databases, data warehouses, and data lakes. Additionally, you can easily connect to other sources or destinations through pre-built API connectors.
• Data Quality Assurance: The tool features robust built-in data quality functionalities that enable data cleansing, profiling, and validation. You can also define data quality rules to flag erroneous records for subsequent review.
• Data Security and Governance: Astera’s ecosystem enhances data integrity and privacy through advanced security and data governance mechanisms, deterring unauthorized access or potential breaches.

Pricing: Astera offers custom pricing according to your specific data integration and management use case and needs. Contact us to get a quote.

Integrate.io

Integrate.io is an ETL tool designed for data integration, and transformation. The tool comes with a range of customization, integration templates, monitoring and logging, feature as well as CDC capabilities, available through different pricing packages.

Key features of Integrate.io:

• Data Source Compatibility:io supports various data sources, including databases, cloud services, web apps, and flat files.
• Transformation Functions: The tool comes with data cleaning, enrichment, and transformation capabilities.
• Cloud Integration:io offers scalability and easily integrates with cloud platforms.

Pricing: Credit-based with 4 tiers. Starts at $3/credit.

Fivetran

Fivetran is a data movement platform that automates the extraction and loading of data from various source systems into a centralized data warehouse or destination. The tool supports the ETL process via dbt, allowing you to access and analyze your data for analytics purposes.

Key features of Fivetran:

• Broad Source Compatibility: Fivetran supports a range of data sources, including databases, cloud services, applications, and APIs.
• Schema Mapping and Transformation: It offers schema mapping and basic data transformation.
• Monitoring and Alerts: The tool includes monitoring and alerting features to track data pipeline performance and detect issues.

Pricing: 4 tiers. Free trial available for every tier.

Talend

Talend (acquired by Qlik) is a data integration and transformation platform that assists organizations in ingesting, cleansing, converting, and moving data from diverse sources into a target destination. The platform is compatible with on-premises and cloud-based data sources.

Key features of Talend:

• Talend provides a range of data transformation capabilities for cleaning and enriching data.
• Users can get both data integration and governance features within a single platform.
• The tool offers an extensive range of connectors and adaptors for various data sources and platforms to support integration.

Pricing: Variable, based on 4 tiers.

Hevo Data

Hevo Data is an ETL platform that supports data integration, movement, and processing. Like other ETL tools, it supports a wide array of data sources and destinations.

Key features of Hevo Data:

• Hevo provides both Python-based and pre-built transformations.
• It provides near real-time data movement capabilities.
• The tool also has monitoring and alerting features that allow you to track ETL job performance and receive notifications about any anomalies.

Pricing: 4 tiers. Free tier available.

Skyvia

Skyvia is an ETL platform that allows businesses to automate data extraction from various sources, perform data transformations, and load it into target destinations for data integration and processing.

Key features of Skyvia:

• The platform supports incremental data updates, reducing the need for full data transfers during ETL.
• Skyvia includes error-handling mechanisms to identify and manage issues during data integration.
• The tool supports data archiving, allowing organizations to securely store historical data for compliance and historical analysis.

Pricing: 5 tiers: Free tier available. Next tier starts at $79/month.

SAS Data Management

SAS Data Management provides ETL capabilities for integrating data from diverse sources, such as databases, CRM platforms, and more. It allows you to perform data extraction from various file formats, apply transformations to meet desired formats and standards and load the processed data into target systems for analysis and reporting.

Key features of SAS Data Management:

• The platform provides metadata management to document and track data lineage.
• It supports both real-time and batch ETL processing to meet various data integration requirements.
• The platform includes error handling mechanisms and logging features to troubleshoot ETL issues.

Pricing: Available on request.

Pentaho

Pentaho is an open-source ETL platform that enables businesses to perform data integration and analytics. The platform has a free community edition, but it also offers a commercial license for enterprises. It supports various processes such as ingestion, cleansing, standardization, and storage.

Key features of Pentaho:

• You can extend Pentaho’s ETL capabilities with custom plugins and scripts for greater customization. However, it requires technical expertise.
• Pentaho supports integration with big data technologies like Hadoop, so you can process large datasets.
• The platform includes data quality features to clean and validate data during ETL processes.

Pricing: Available on request.

Stitch

Stitch is a cloud-based data integration service that enables ETL processes. It provides a platform for extracting, transforming, and loading data from various sources into the destination of choice.

Key features of Stitch:

•  Stitch supports ETL from various data sources, including databases, cloud applications, and APIs.
• The tool comes with automated and scheduled data replication capabilities to update data.
• It is designed as a cloud-native ETL service that can accommodate changing data needs.

Pricing: 3 tiers, available both monthly and annually. Starts at $100.

Blendo

Blendo is a self-service ETL tool that provides access to various cloud data sources. Using Blendo, you can automate data transformation as well as transfer raw data sets into the database or a cloud data warehouse of choice.

Key features of Blendo:

• Blendo supports connectivity to Redshift, BigQuery, and other data warehouses.
• It offers the ability to automate the entire ETL process.
• Blendo is designed to scale with evolving data requirements.

Pricing: Starting at $250/month. Free trial available.

Airbyte

Airbyte is an open-source data integration tool. It allows users to ETL/ELT their data to various data lakes, warehouses, and databases. It specializes in data movement and requires external tools, such as dbt, to transform data.

Key features of Airbyte:

• RAG and unstructured data integration for loading unstructured data.
• Connectivity to various databases.
• Data security and governance for deployment models.

Price: Tier-based with 4 tiers. Open-source tier is free. Cloud tier is priced based on volume of data replicated.

Azure Data Factory

Azure Data Factory is Microsoft’s cloud-based service for creating and managing data flows on the cloud. It enables both programmatic and UI-based approaches to handling data.

Key features of Azure Data Factory:

• Data preview and validation.
• Custom event triggers for ETL
• Security features including role-based access controls.

Price: Variable. Based on: Pipeline, data flow, and data factory operations.

Oracle Data Integrator

Oracle Data Integrator (ODI) is Oracle’s offering for all data integration processes, including ETL. It provides support for various integration requirements and is compatible with Oracle Warehouse Builder (OWB) and Oracle Enterprise Manager.

Key features of Oracle Data Integrator:

• SOA-enabled data services.
• ETL with Big data support.
• Parallel processing for improved ETL

Price: Variable. Based on GBs consumed, workspace usage, pipeline execution,a and OCI streaming.

Apache Airflow

Apache Airflow is another open-source tool with support for ETL. It utilizes Python frameworks for managing data pipelines, allowing ETL workflows to be dynamic and extensible

Key features of Apache Airflow:

• Workflow parameterization using Jinja engine.
• Multiple workflow automation options.
• Visual record of all workflows and pipelines tasks.

Price: Open-source/free.

Portable.io

Portable is a cloud data integration software that provides connectivity to many sources and can design custom integrations on demand. Portable.io can also ELT/ELT data to various major databases.

Key features of Portable:

• Data replication across many long-tail sources.
• Dedicated 24×7 customer support for source data changes.
• Free development and running of new connectors.

Price: 3 tiers. Starter, Scale, and Enterprise. Pricing starts at $290 month.

Features to Look for in an ETL Tool

Before you invest in an ETL platform, you must evaluate its capabilities & features to determine whether it’ll meet your data management requirements. Here are some important features that an ETL solution should have:

1. Data Extraction: An effective ETL tool should have the ability to connect to a wide range of data sources, including databases (SQL, NoSQL), APIs, and various file formats (CSV, JSON, XML). It should also support unstructured data extraction, so you can easily extract data from PDF and scanned documents to optimize data transfer and reduce processing time.
2. Library of Connectors: Modern ETL tools offer an expansive library of connectors, including file formats, databases, and cloud platforms. Ensure that the tool you purchase can natively support your data sources.
3. Ease of Use: Managing custom-coded ETL mappings is a complex process that requires deep development expertise. To save developer resources and transfer data from the hands of developers to business users, you need an enterprise ETL solution that offers an intuitive, code-free environment to extract, transform, and load data.
4. Data Transformations: Data transformation needs vary from simple transformations such as lookups and joins to more complex tasks like denormalizing data or converting unstructured data into structured tables. You should select an ETL tool that offers a range of simple and more advanced transformations as per your data manipulation requirements.
5. Data Quality and Profiling: You only want clean and accurate data to be loaded into your repository. So, prioritize data quality management, and look for an ETL platform that offers inbuilt data quality and profiling capabilities to determine enterprise data’s consistency, accuracy, and completeness.
6. Automation: Large enterprises must handle hundreds of ETL jobs daily, which is only possible through automation. Look for an advanced ETL automation solution with end-to-end automation capabilities, including job scheduling and process orchestration, to streamline the data management processes.
7. Monitoring and Logging: Comprehensive monitoring features are vital for keeping track of ETL job performance. Look for tools that offer detailed logging of job execution, error handling, and notifications. This allows you to identify and address issues promptly, ensuring data quality and reliability.
8. Scalability and Performance: An ETL tool should offer parallel processing capabilities to handle large data sets. Parallel processing splits tasks into smaller units and processes them simultaneously, significantly reducing processing times. Additionally, tools should have optimization features like query optimization and memory management to enhance performance.

How to Select the Right ETL Tool?

Selecting the right ETL tool is a crucial decision that can significantly impact a company’s data integration and analytics capabilities. Here’s how to choose the most suitable ETL tool:

Define Your Requirements

Begin by clearly defining your organization’s ETL requirements. Which data sources do you need to integrate? What types of transformations are necessary? What is the volume of data you’re dealing with, and what are the expected growth rates? Consider your organization’s long-term goals and scalability requirements.

Evaluate Data Sources and Formats

Take stock of the data sources you have. Ensure that the ETL tool you choose can connect to and ingest data from these sources, whether they are databases, cloud services, web services, or flat files. Verify that the tool supports the data formats commonly used in your organization, such as CSV, JSON, XML, or proprietary formats.

Assess Data Transformation Capabilities

Consider the complexity of data transformations required for your business processes. Look for ETL tools that offer the necessary transformation functions and capabilities to meet your needs. Evaluate the tool’s support for handling data quality, data cleansing, and error handling to ensure the reliability of transformed data.

Scalability and Performance

Analyze the tool’s scalability and performance capabilities. Will it handle your current data volumes efficiently, and can it scale as your data grows? Look for features like parallel processing, distributed computing, and in-memory processing that can improve ETL performance.

Ease of Use and User-Friendliness

Consider the technical expertise of your team. Choose ETL tools that match the skill set of your staff. Evaluate the tool’s user interface for ease of use, as well as its support for no-code ETL development. A no-code solution can provide substantial cost savings in the long run. This is because hiring technical resources to manage and maintain ETL pipelines can be costly.

Integration with Existing Systems

Ensure that the selected ETL tool integrates smoothly with your existing systems, such as data warehouses, BI tools, and analytics platforms. Compatibility with your technology stack is essential for a seamless data ecosystem. Many enterprises opt for a solution that provides a unified, end-to-end data ecosystem to avoid working with multiple vendors.

Security and Compliance

Assess the tool’s security features, including data encryption, access controls, and compliance certifications (e.g., GDPR, HIPAA). Ensure that it aligns with your organization’s data security and compliance requirements. Also, the ETL tool should support effective data governance practices to ensure that data security measures align with organizational data policies.

Automate ETL Processes with Astera Centerprise

 

Astera Centerprise is an enterprise-grade, code-free data management solution with a powerful ETL/ELT engine. Our zero-code solution has a vast library of connectors, transformations, and in-built functionalities, making it easier for users to extract, manipulate and load data to the destination of choice without writing code. Our tool’s automation and orchestration capabilities can save up to 80% time required to manage ETL processes.

Interested in trying Astera Centerprise and exploring how it meets your unique ETL requirements? Access a free 14-day trial version and experience it first-hand!