21 Top Data Integration Tools

Data powers everything in modern businesses—from real-time analytics to automation. The right data integration tool can make all the difference, helping you stay ahead of the competition. But with so many options out there, picking the best one can feel overwhelming.

That’s where this list comes in. We’ve rounded up 21 of the best data integration tools to help you streamline your workflows, move data seamlessly, and make smarter decisions.

Let’s dive in!

Understanding Data Integration

Data integration is merging data from diverse sources to create a cohesive, comprehensive dataset that gives you a unified view. By consolidating data across multiple sources, your organization can discover insights and patterns that might remain hidden while examining data from individual sources alone. Transferring data from platforms like Salesforce to Redshift requires a strong data integration tool to manage large volumes and complex data transformations seamlessly.

What are Data Integration Tools?

These are software solutions that combine data from various sources into a unified view, making it easier to analyze and use. They work by connecting to different databases, applications, and systems, gathering data, and transforming it into a compatible format. These tools streamline data movement, ensure data consistency, and eliminate duplicates. They are commonly used for reporting, analytics, and creating a single source of truth, enabling organizations to make more informed decisions by having all their data accessible and organized in one place.

Take a look at how data integration works in detail to get a better understanding.

Features

• Data Connectivity: Connects to various data sources like databases, cloud apps, and APIs.
• Data Transformation: Cleans, formats, and standardizes data for compatibility.
• Real-time Sync: Updates data in real-time to keep information current.
• Data Quality Checks: Detects and resolves data inconsistencies and duplicates.
• Scalability: Handles large data volumes and supports growing data needs.

Also, check out data integration techniques to dive deeper into how data integration functions.

Types of Integration Tools

• ETL Tools: Extract, transform, and load data from one source to another.
• Data Replication Tools: Copy data from one system to another for backup or analytics.
• Data Virtualization Tools: Access and query data without moving it, creating a “virtual” database.
• iPaaS (Integration Platform as a Service): Cloud-based platforms that connect applications and data across environments.
• Streaming Data Tools: Process and integrate data in real-time as it’s generated.

Discover the differences between Data Integration and ETL to get a better understanding of the concepts

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Top 21 Data Integration Tools

1. Hevo Data

Why Choose Hevo?

Hevo Data stands out for its no-code data pipeline capabilities, making it perfect for teams without extensive technical expertise. The platform supports 150+ integrations, including cloud data warehouses like Snowflake and BigQuery. The best part is that Hevo can automatically detect and adapt to schema changes—saving you hours of manual intervention.

Key features of Hevo Data

• Hevo ensures zero data loss, always keeping your data intact.
• It lets you monitor your workflow and stay in control with enhanced visibility and reliability to identify and address issues before they escalate.
• Hevo provides you with 24/7 customer support to ensure you enjoy round-the-clock support when needed.

Pros	Cons
– Real-time data streaming. – Automatic schema management. – Transparent and tier-based pricing	– Extremely large datasets may take longer time to replicate.

2. SAP

Why Choose SAP?

SAP is ideal for large enterprises looking to integrate data from complex environments. It’s a powerful solution with deep integration with SAP ERP systems and other business applications.

Key Features of SAP

• Connect to data from SAP and third-party sources, and process structured and unstructured data 
• Transform, cleanse, match, and consolidate data to ensure data quality. 
• Improve performance and scale to meet high-volume data needs 
• Extract meaning from unstructured text data 

Pros	Cons
– Strong integration with SAP environments – Ideal for enterprise-level needs – Powerful data transformation and governance features	– Lack of transparent pricing – Steep learning curve for new users – Can be expensive for smaller companies

3. Jitterbit

Why choose Jitterbit?

Jitterbit is impressive  with its combination of API management and integration capabilities. It’s ideal for businesses transitioning to digital ecosystems. Unlike traditional ETL tools, Jitterbit’s ability to build, deploy, and manage APIs in minutes sets it apart.

Key Features of Jitterbit

• Jitterbit offers a powerful Workflow Designer that allows you to create new integration between two apps with its pre-built data integration tool templates.
• It has an automapper that can help you map similar fields and over 300 formulas to simplify the transformation task.
• Jitterbit provides a virtual environment where you can test integrations without disrupting existing ones.

Pros	Cons
– Hybrid cloud/on-premise integration – API gateway for real-time connections – User-friendly with pre-built templates- Transparent pricing	– Limited scalability for very large datasets. – Custom scripting sometimes needed.

4. Adverity

Why Choose Adverity?

Adverity is the best choice for handling marketing and advertising data. Unlike generic tools, it offers industry-specific integrations for platforms like Google Ads, Facebook, and HubSpot. It’s analytics capabilities can make  campaign optimization much simpler for you.

Key Features of Adverity

• Adverity excels in data transformation and quality monitoring, automating the process of cleaning and unifying data from various sources.
• With AI-powered features, it intelligently integrates and manages data, offering robust data governance features that help ensure high-quality data for high-quality insights.
• Adverity also allows teams to easily manage where data is shared and who it is shared with, all from a single platform. 

Pros	Cons
– Marketing-focused integrations – AI-powered insights – Centralized dashboards – Supports numerous marketing platforms	– Narrow focus on marketing data – Expensive for SMBs

5. Celigo

Why Choose Celigo?

Celigo shines in SaaS application integrations, especially for e-commerce businesses. It allows you to automate processes between Shopify, NetSuite, and Salesforce without writing a single line of code. 

Key Features of Celigo

• Celigo offers a low-code GUI-based Flow Builder that allows you to build custom integrations from scratch. 
• It provides an Autopilot feature with inegrator.io that allows you to automate most workflow with the help of pattern recognition AI.
• Using Celigo, developers like you can create and share your stacks and generate tokens for direct API calls for complex flow logic to build integrations.

Pros	Cons
– Pre-built SaaS connectors – Intuitive interface – Automation for e-commerce – Transparent pricing	– Limited customization for advanced workflows – Best suited for SaaS/mid-sized organizations

6. Microsoft Azure Data Factory

Why Choose ADF?

Azure Data Factory is one of my favorite choices for cloud-based ETL and ELT processes. Its integration with the Azure ecosystem allows to connect on-premise data with cloud services effortlessly. 

Key Features of the Microsoft Azure Data Factory

• Data Factory offers a versatile integration and transformation platform that seamlessly supports and speeds up your digital transformation project using intuitive, code-free data flows.
• Using built-in connectors, you can ingest all your data from diverse and multiple sources.
• SQL Server Integration Services (SSIS) can be easily rehosted to build code-free ETL and ELT pipelines with built-in Git, supporting continuous integration and continuous delivery (CI/CD).

Pros	Cons
– Strong Azure ecosystem integration – Scalable cloud-based ETL – Cost-effective pay-as-you-go pricing – Handles structured/unstructured data	– Limited no-code interface – Requires advanced Azure knowledge

7. MuleSoft

Why Choose MuleSoft?

MuleSoft’s API-led connectivity approach makes it the perfect choice for enterprises aiming for an integrated, unified data ecosystem. Its ability to connect cloud and on-premise systems sets it apart for large-scale integration projects.

Key Features of the MuleSoft Anypoint Platform

• It offers mobile support that allows you to manage your workflow and monitor tasks from backend systems, legacy systems, and SaaS applications.
• MuleSoft can integrate with many enterprise solutions and IoT devices such as sensors, medical devices, etc.
• It allows you to perform complex integrations with pre-built templates and out-of-box connectors to accelerate the entire data transfer process.

Pros	Cons
– API-led connectivity – Hybrid for cloud/on-premise – Extensive pre-built connectors- Scalable for enterprises	– High cost – Complex setup process

8. Informatica

Why I Choose Informatica?

Informatica was my go-to for complex data governance and metadata management projects. Its robust AI capabilities give deeper insights into data and allow for extensive automation.

Key Features of Informatica PowerCenter

• You can easily manage and monitor your data pipelines and quickly identify and address any issues that might arise.
• You can ensure high data quality and accuracy using data cleansing, profiling, and standardization.
• An extensive catalog of related products for big data integration, cloud application integration, master data management, data cleansing, and other data management functions complements it.

Pros	Cons
– Comprehensive data governance – Reliable real-time/batch processing – Extensive on-premise/cloud support – Ideal for complex workflows	– Expensive – Requires technical expertise

9. Dell Boomi

Why Choose Boomi?

Dell Boomi is exceptional for quick application and data integration. Its low-code platform allowed my team to build integrations faster than traditional coding methods.

Key Features of Dell Boomi

• Whether you’re an SMB or a large company, you can use this tool to support several application integrations as a service.
• With Dell Boomi, you can access a variety of integration and data management capabilities, including private-cloud, on-premise, and public-cloud endpoint connectors and robust ETL support.
• The tool allows your business to manage Data Integration in a central place via a unified reporting portal.

Pros	Cons
– Hybrid platform with cloud capabilities – Pre-built templates – Scalable and user-friendly – Transparent pricing	– Limited advanced on-premise support – Occasional performance bottlenecks

10. Pentaho Data Integrator

Why Choose Pentaho?

Pentaho is a strong open-source option for data integration, especially for businesses that need flexibility. Its combination of ETL, reporting, and analytics capabilities make it a versatile tool in many environments.

Key Features of Pentaho

• Pentaho Data Integration (PDI) is known for its simple learning curve and simplicity of usage.
• You can use Pentaho for multiple use cases that it supports outside of ETL in a Data Warehouse, such as database replication, database to flat files, and more.
• Pentaho allows you to create ETL jobs on a graphical interface without writing code.

Pros	Cons
– Open-source version available – Strong reporting/visualization – Cloud and on-premise support – Customizable ETL workflows	– Lacks native SaaS connectors – Limited support for the community edition

11. AWS Glue

Why Choose AWS Glue?

AWS Glue is an excellent choice for cloud-native organizations already leveraging AWS services. It’s a fully managed ETL service that automates much of the work, saving time on manual configurations.

Key Features of the AWS Glue

• You don’t have to write the code to create and run ETL jobs; this can be done simply by using AWS Glue Studio. 
• Using AWS Glue, you can execute serverless ETL jobs. Also, other AWS services like S3, RDS, and Redshift can be integrated easily.
• Your data sources can be crawled and cataloged automatically using AWS Glue. 

Pros	Cons
– Serverless ETL fully integrated with AWS – Automatic schema discovery – Pay-as-you-go pricing- Effortless scaling	– Best suited for AWS users – No no-code functionality

12. SnapLogic

Why Choose SnapLogic?

SnapLogic is built for speed, offering an easy-to-use interface with drag-and-drop features. Its ability to handle batch and real-time data makes it an attractive option for fast-paced businesses.

Key Features of SnapLogic

• SnapLogic offers reporting tools that allow you to view the progress of the ETL job with the help of graphs and charts.
• It provides the simplest user interface, enabling you to have self-service integration. Anyone with no technical knowledge can integrate the source with the destination.
• SnapLogic’s intelligent system detects any EDI error, instantly notifies you, and prepares a log report for the issue.

Pros	Cons
– AI-powered automation – Extensive pre-built connectors – Scalable for large enterprises – Intuitive drag-and-drop interface	– High cost – Performance issues with very complex workflows

13. Talend

Why Choose Talend?

Talend is an open-source and cloud-based integration platform, ideal for businesses that want powerful data transformation tools without the heavy cost. It stands out for its flexibility and strong data governance features.

Key Features of Talend

• Talend also offers a wide array of services for advanced Data Integration, Management, Quality, and more. However, we are specifically referring to Talend Open Studio here.
• Your business can install and build a setup for both on-premise and cloud ETL jobs using Spark, Hadoop, and NoSQL Databases.
• To prepare data, your real-time team collaborations are permitted. 

Pros	Cons
– Open-source version available – Strong data governance – Broad compatibility for systems – No-code functionality	– Performance issues with large datasets – Steeper learning curve for enterprise tools

14. IBM DataStage

Why Choose DataStage?

IBM Infosphere DataStage is a powerful option for large enterprises that need a comprehensive ETL platform. It’s beneficial for businesses managing large-scale, complex data environments.

Key Features of IBM DataStage

• To integrate your structured, unstructured, and semi-structured data, you can use Data Stage.
• The platform provides a range of data quality features for you, including data profiling, standardization, matching, enhancement, and real-time data quality monitoring.
• By transforming large volumes of raw data, you can extract high-quality, usable information and ensure consistent and assimilated data for efficient data integrations. 

Pros	Cons
– Enterprise-grade for large organizations – Excellent for big data – Real-time data integration – Strong governance tools	– Very expensive – Requires technical expertise

15. Oracle Data Integrator

Why Choose ODI?

Oracle Data Integrator is a go-to for enterprises deeply embedded in the Oracle ecosystem. Its suite offers a comprehensive range of features from data integration to governance.

Key Features of Oracle Data Integrator 

• It automatically detects faulty data during your data loading and transforming process and recycles it before loading it again.
• It supports all RDBMSs, such as Oracle, Exadata, Teradata, IBM DB2, Netezza, Sybase IQ, and other file technologies, such as XML and ERPs.
• Its unique ETL architecture offers you greater productivity with low maintenance and higher performance for data transformation.

Pros	Cons
– Seamless integration with the Oracle ecosystem – Strong data security – Scalable for large workloads – Extensive analytics	– High licensing costs – Limited flexibility for non-Oracle environments

16. Astera

Why Choose Astera?

Astera is an AI-powered unified data management platform with both on-prem and cloud-based solutions. Besides its data integration solution Data Pipeline Builder, Astera also offers tools for unstructured data management, data warehousing, and API and EDI management. The platform’s no-code, intuitive interface makes it equally accessible for business and technical users alike.

Key Features of Astera

• Built-in features to validate data and ensure data quality.
• Native connectors and extensive transformations to support a variety of use cases.
• Powerful, enterprise-grade ETL engine to ensure scalability for growing data volumes.

Pros	Cons
– Excellent customer support – Easy-to-use UI – Simplifies EDI tracking – Frequent updates with strong security	– Lacks comprehensive documentation – Key features limited to Enterprise Edition

17. Integrate.io

Why Choose Integrate.io?

Integrate.io (formerly known as Xplenty) is a cloud-based data integration platform ideal for users looking for both an intuitive UI and robust data processing capabilities. It’s especially great for businesses transitioning to the cloud.

Key Features of Integrate.io:

• Integrate.io offers a low-code, simple drag-and-drop user interface and transformation features – like sort, join, filter, select, limit, clone, etc. —that simplify the ETL and ELT process.
• Integrate.io provides a REST API connector that allows users to connect to and extract data from any REST API. 
• Integrate.io’s low-code and no-code workflow creation interface allows you to specify the order of actions to be completed and the circumstances under which they should be completed using dropdown choices.

Pros	Cons
– User-friendly no-code ETL – Pre-built templates – Transparent pricing – Excellent support for SaaS applications	– Limited support for on-prem systems – Less suitable for complex enterprise workflows

18. Skyvia

Why Choose Skyvia?

Skyvia offers a simple, cost-effective solution for small to mid-sized businesses looking for an intuitive platform for data integration, backup, and synchronization.

Key Features of Skyvia:

• Provides a user-friendly interface with wizards and intuitive tools for data integration across databases and cloud applications, eliminating the need for coding.
• Offers a range of pricing plans to accommodate businesses of all sizes and budgets.
• Hosted on a reliable and secure Azure cloud infrastructure, ensuring continuous data access and minimal downtime.
• Enables secure access to on-premises data sources without complex network configurations.

Pros	Cons
– Affordable for SMBs – Pre-built SaaS connectors – Simple no-code interface – Transparent pricing	– Limited support for on-premise systems – Limited features for enterprise-scale projects – Less robust automation tools

19. Matillion

Why Choose Matillion?

Matillion is a cloud-based ETL tool designed to be used with modern data warehouses like Amazon Redshift, Google BigQuery, and Snowflake. Its speed and focus on cloud environments make it a favorite for companies scaling their data operations.

Key Features of Matillion:

• Provides a user-friendly interface with wizards and intuitive tools for data integration across databases and cloud applications, eliminating the need for coding.
• Offers a range of pricing plans to accommodate businesses of all sizes and budgets.
• Hosted on a reliable and secure Azure cloud infrastructure, ensuring continuous data access and minimal downtime.
• Enables secure access to on-premises data sources without complex network configurations.

Pros	Cons
– Cloud-native integration – Strong support for cloud data warehouses – Simple UI – Pricing is usage-based	– Limited advanced workflow customization – Focused on cloud; lacks hybrid support

20. Fivetran

Why Choose Fivetran?

Fivetran is a fully managed data integration service that excels in replicating data from a variety of sources into your data warehouse. It’s particularly beneficial for businesses with heavy cloud data usage.

Key Features of Fivetran:

• Provides a user-friendly interface with wizards and intuitive tools for data integration across databases and cloud applications, eliminating the need for coding.
• Offers a range of pricing plans to accommodate businesses of all sizes and budgets.
• Hosted on a reliable and secure Azure cloud infrastructure, ensuring continuous data access and minimal downtime.
• Enables secure access to on-premises data sources without complex network configurations.

Pros	Cons
– Fully automated ETL – Extensive SaaS integrations – Real-time syncing	– High cost for large data volumes – Limited transformation capabilities – Confusing pricing

21. Airflow

Why Choose Airflow?

Apache Airflow is a highly flexible open-source tool designed to orchestrate complex workflows and data pipelines. I chose it because of its strong scheduling capabilities, wide adoption in the data engineering community, and the ability to scale seamlessly for any size of operation. It’s perfect for teams who need complete control over their data pipeline orchestration.

Key Features of Airflow:

• Deploying Airflow requires just a little knowledge of Python.
• It is an open-source platform, making it free to use and resulting in many active users.
• Platforms like Google Cloud, Amazon AWS, and many more can be readily integrated using the available integrations. 
• Beginner-level knowledge of Python is sufficient to create complex workflows on airflow.

Pros	Cons
– Free to use and customizable. – Supports complex workflows with custom operators and hooks. – Active community with plugins and integrations.	– Can be complex for new users to set up. – Requires regular upkeep and management. – Lacks a polished user interface compared to some paid tools.

How to Choose the Right Data Integration Tools for your Needs?

While picking the right Data Integration tool from several great options out there, it is essential to be wise enough. So, how would you select the best data integration platform for your use case? Here are some factors to keep in mind:

1) Data Sources Supported

As your business grows, the complexity of the data integration strategy will grow. Take note that there are many streams and web-based applications, and data sources that are being added to your business suit daily by different teams.

Hence, it is important to choose a tool that could grow and can accommodate your expanding list of data sources as well.

2) Scalability

Initially, the volume of the data you need for your data integration software could be less. But, as your business scales, you will start capturing every touchpoint of your customers, exponentially growing the volume of data that your data infrastructure should be capable of handling.

When you choose your Data Integration tool, ensure that the tool can easily scale up and down as per your data needs.

3) Security and Compliance

Given you are dealing with mission-critical data, you have to make sure that the solution offers the expertise and the resources needed to ensure that you are covered when it comes to security and compliance.

4) Real-Time Data Availability

This is applicable only if you are use case is to bring data to your destination for real-time analysis. For many companies –  this is the primary use case. Not all data integration solutions support this. Many bring data to the destination in batches – creating a lag of anywhere between a few hours to days.

5) Data Transformations

The data that is extracted from different applications is in different formats. For example, the date represented in your database can be in epoch time whereas another system has the date in “mm-dd-yy”.

To be able to do meaningful analysis, companies would want to bring data to the destination in a common format that makes analysis easy and fast. This is where Data transformation comes into play. Depending on your use case, pick a tool that enables seamless data transformations.

Combining data discovery tools with data integration processes ensures that no critical data source is overlooked during the integration process.

Also, check out the architecture of data integration to get a clearer idea of what you are working with.

Benefits of Data Integration Tools

Now that you have the right tools based on your use case, it is time to learn how they benefit your business. The benefits range from: 

1. Improved Decision-Making: Since the raw data is now converted into usable information and data is consolidated, your decisions based on that information will be faster and more accurate.
2. Automated Business Processes: Using these tools, your data integration task becomes automated, leaving you and your team more time to focus on business development-related activities. 
3. Reduced Costs: By utilizing these tools, the integration processes are automated, so manual efforts and errors are significantly reduced, therefore reducing the overall cost. 
4. Enhanced Compliance and Security: These tools ensure that the data handled follows proper regulatory standards and that any sensitive information is protected. 
5. Increased Agility and Collaboration: You can easily share your data and collaborate across departments without interruptions, boosting the data’s overall agility and responsiveness. 

You can also take a look at our detailed guide on marketing data integration to learn how to unify data from multiple marketing platforms for better insights.

Conclusion

This article provided you with a brief overview of Data Integration and Data Integration Tools, along with the factors to consider while choosing these tools. You are now in the position to choose the best Data Integration tools based on your requirements.

Several great options are available, including tools like Informatica, Boomi, and AWS Glue, each catering to different needs. However, if you’re looking for a fully managed, no-code platform that supports real-time data integration and transformation, Hevo Data stands out as a reliable choice. With its intuitive interface and wide range of connectors, Hevo can help you simplify your data integration process and scale effortlessly. Sign up for Hevo’s 14-day free trial and experience seamless data migration.

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