16 Best Data Integration Tools in 2024 [Updated]

Effective data integration tools are the backbone of modern analytics and operational efficiency. The right platform doesn't just connect data sources; it transforms raw data through ETL (Extract, Transform, Load), ELT (Extract, Load, Transform), and CDC (Change Data Capture) into actionable insights, empowering businesses to make informed decisions and stay ahead of the competition.

Navigating the landscape of data integration tools can be challenging, with each offering unique features, strengths, and complexities. This guide is designed for two key audiences:

• Businesses looking to adopt a data integration platform for the first time.
• Organizations considering switching to a new data integration tool to better meet their needs.

We’ve carefully selected the top 16 data integration platforms for 2024, each offering unique strengths that could be the perfect fit for your organization. Whether you're prioritizing robust ETL processes, real-time ELT capabilities, or seamless CDC for continuous data synchronization, this guide will provide you with a detailed overview of each tool’s pros, cons, and suitability for your specific requirements.

We’re continuously updating this guide with the latest insights and user experiences. Share your thoughts and experiences on our Estuary Slack community or contact us to help us make this guide even better.

What is Data Integration?

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Data integration is the process of combining data from various sources and loading it into designated destinations, such as data warehouses or data lakes. This process enables you to synchronize data across different systems, ensuring consistency and accuracy. By integrating your data, you can manage it more efficiently, derive meaningful insights, and transform raw information into actionable business intelligence.

The data integration process for analytics involves the following steps:

• Determine Your Data Requirements: Understand what data is needed and for what purpose.
  
• Collect, Consolidate, Transform, and Load Data: Gather data from multiple sources, clean and transform it as needed, and load it into the desired destination using ETL Tools. These tools help automate and streamline the process, making it more efficient and less prone to errors.
  
• Structure Data for Reporting and Analysis: Organize the data in a way that supports effective reporting and analysis.

To dive deeper into data integration, explore these related topics:

• Challenges of Data Integration
• Benefits of Data Integration
• Data Integration Strategies

What are Data Integration Tools?

Data integration tools are software applications that combine data from different sources, such as databases, applications, and cloud services, into a unified view. These tools enable businesses to move, clean, and transform data, ensuring it is accessible and usable for analytics, reporting, and decision-making. They typically support ETL, ELT, and CDC processes, providing flexibility to choose the best approach for your needs.

These tools play a crucial role in maintaining data consistency, improving data quality, and enabling real-time data synchronization across systems. Whether you’re managing data for a small business or a large enterprise, data integration tools help streamline data workflows and enhance operational efficiency.

16 Top Data Integration Tools to Watch in 2024

Here are the 16 best data integration tools to watch in 2024, helping businesses streamline data workflows with advanced ETL, ELT, and CDC capabilities.

1. Estuary

Estuary Flow is our comprehensive, flexible, and scalable data integration platform with powerful real-time ETL, ELT, and CDC capabilities. This top-tier data pipeline tool has an easy-to-use interface for instant data transfer and seamlessly integrates batch and real-time data for instantaneous data transfer from a variety of databases, SaaS, filestores, and other sources

Estuary Flow’s powerful data transformation capabilities allow you to clean, transform, and enrich your data. This ensures that your data is accurate and ready for analysis. We use industry-standard security measures to protect your data, including encryption, authentication, and authorization. 

Flow is a reliable platform designed to meet the needs of even the most demanding businesses. It provides a simple no-code to to create, manage, and monitor data flows. If you want to sync data across different systems in real time, Flow is an excellent choice. It’s easy to connect to a wide range of data sources and destinations since it supports many connectors.

Pros

• No-code end-to-end data integration using a Web-based UI, or through coding using a command line interface (CLI)
  
• Real-time change data capture and streaming or batch from sources for data replication and database migration
  
• Streaming ETL transformations using SQL and TypeScript
  
• Data storage for later data replay, backfilling, and time travel
  
• Support for loading multiple destinations with a single pipeline
  
• Support for ELT using dbt with destinations that support dbt.
  
• A low-latency, scalable platform suitable for businesses of all sizes
  
• Includes data governance and security features for sensitive data
  
• Supports data automating for schema changes (schema evolution)
  
• Open source with private cloud and public cloud deployment options.

Cons

• Estuary Flow is a relatively new company compared to some other vendors

Pricing

Flow offers these flexible pricing plans:

• Free: Up to 2 connectors and 10 GB/month
  
• Cloud (30-day free trail): $0.50/GB change data moved +$0.14/hour/connector
  
• Enterprise (Custom pricing): Enterprise pricing available

If you want to get your data where you want it in milliseconds, try Estuary Flow for free. It provides a comprehensive data integration platform that is suitable for a variety of data integration tasks. 

2. SQL Server Integration Services 

SQL Server Integration Services (SSIS) is a part of the Microsoft SQL Server and is used for various data replication and integration tasks. SSIS is known for its speed and flexibility in a data warehouse environment, making it adept at tasks like data extraction, loading, and transformation.

SSIS supports data sources like SQL Server, Excel files, Oracle, and IBM DB2. It comes with graphical tools and wizards for workflow functions, like sending email messages, FTP operations, and setting data sources and destinations.

Pros

• Robust error and event handling
  
• Assists in cleaning and standardizing data
  
• Automates administrative functions and data loading
  
• Includes a graphical user interface (GUI) for easy data transformation
  
• Streamlines the process of populating data marts and data warehouses

Cons

• Potential issues in non-windows environments
  
• Limited support for alternative data integration styles

Pricing

Custom pricing plans are available on demand.

3. Qlik

Qlik provides both on-premise and cloud data integration services focused on automating real-time data delivery and transformation. It updates your data automatically and saves you from job scheduling or scripting. 

It works with data sources like relational databases, SAP, mainframes, and SaaS applications, and it's compatible with platforms like Snowflake Data Cloud and Databricks. It’s highly effective for tasks like analytics, machine learning, and digital transformation.

Qlik also provides services like data transformation, application automation, catalog and lineage tracking, and superior data architecture.

Pros

• Point-and-click pipeline configuration
  
• Provides full data lifecycle understanding and monitoring
  
• No-code interface for data transformation and workflow creation
  
• Real-time data movement from hundreds of sources to top cloud platforms
  
• Robust data architecture with scalability, security, and maintenance benefits

Cons

• Connection losses require a full reload
  
• The interface may be less intuitive for some users
  
• The help portal can be challenging to navigate for specific information

Pricing

Pricing plans for both on-premise and cloud solutions are available on demand.

4. Informatica PowerCenter

Informatica PowerCenter is a GUI-based data integration tool. It’s a comprehensive platform that you can use for data integration, migration, and validation. You can combine all your business data into a trusted, unified view with zero-code data integration.

PowerCenter works on data integration using an ETL architecture. It can connect to and fetch data from multiple heterogeneous sources and perform data processing. Some other PowerCenter solutions include data masking, data virtualization, and master data management.
 

If you have several legacy data sources that are primarily on-premises, Informatica PowerCenter is a good choice.

Pros

• Seamlessly scales with Big Data needs
  
• The debugger option helps identify failure points in data mappings
  
• Pipeline partitioning and push-down optimizations
  
• Helps synchronize geographically distributed team members
  
• Serverless deployment results in zero overhead

Cons

• Suitable mainly for midsize businesses and large enterprises
  
• Slightly expensive
  
• You must adapt your data architecture to the solution’s design

Pricing

Flexible pricing plans start from a base price of $2,000/month.

5. Oracle Data Integrator

Oracle Data Integrator (ODI) is one of the most renowned data integration tools. It provides uninterrupted data access across multiple systems. Whatever could be your data integration requirements, ODI covers it all. You can use it for high-volume, high-performance batch loads, or event-driven trickle-feed integration processes.

ODI features seamless data integration for SaaS and SOA-enabled data services. It also automatically detects faulty data during the data load and transform processes. Upon seeing faulty data, ODI recycles it before loading it again.

If you have an existing Oracle ecosystem with large volumes of data on different sources, consider using ODI.

Pros

• Easy-to-use interface
  
• Vast choice of transformation options
  
• Impressive scalability and performance

Cons

• More expensive than peer integration tools

Pricing

Custom price quotes are available on demand.

6. SAP Data Services

SAP Data Services is an information management layer of SAP’s Business Technology Platform. However, you can use SAP Data Services as a standalone solution as well.

With SAP Data Services, you can access, transform, and connect data to benefit critical business processes. One of the key features of SAP Data Services is that it allows you to process text data. As a result, you can unlock meaningful insights into unstructured data. 

Pros

• Can be used for structured and unstructured data
  
• Simple maintenance
  
• Ready-to-use social media connectors

Cons

• Error descriptions can be improved
  
• Very technical—difficult to use for people without technical knowledge
  
• Debugging process isn’t simple

Pricing

Contact customer support to get a price quote.

7. Airbyte

Airbyte is an open-source data integration tool launched in 2020. It allows businesses to create customizable data pipelines by connecting to over 300 data sources, with a mix of community and officially maintained connectors. While it primarily supports batch data processing, its open-source nature makes it a flexible and cost-effective option for teams looking to control their data workflows.

Pros

• Open-source and flexible: Airbyte provides the freedom to modify and customize your data pipelines, making it a good choice for businesses that want full control over their data integration processes.
• Extensive connector support: With over 300 connectors available, including 50+ actively maintained by Airbyte, the platform supports a wide range of data sources. This includes a large number of community-developed connectors, which ensures that the ecosystem is constantly growing and adapting to the needs of the broader user base.
• Supports dbt for transformations: While Airbyte is focused on data loading, it integrates well with dbt (Data Build Tool) for post-load transformations. This allows businesses to perform complex transformations in their target data warehouse using SQL, making it a powerful option for those who rely on dbt for their transformation layer.

Cons

• Batch processing only: Airbyte only supports batch-based data processing, which means that it may not be suitable for businesses that require real-time data integration. The reliance on batch processing can introduce latency in data updates, making it less ideal for time-sensitive use cases.
• Complex self-hosting: While the self-hosted version is free, managing and maintaining your own infrastructure can be challenging. Self-hosting requires teams to handle updates, troubleshooting, and infrastructure scaling, which can increase the operational burden on small or less technically proficient teams.
• Limited official connector maintenance: Out of the 300+ available connectors, only around 50 are actively maintained by Airbyte. This means that for many data sources, you may be relying on community-driven connectors, which may not always receive timely updates or bug fixes, potentially affecting long-term stability.

Pricing

• Open Source: Free but requires self-hosting, which can add infrastructure and management costs.
• Cloud: Starts at $2.50 per credit, but costs can escalate quickly with higher usage, making it less predictable.
• Enterprise: Custom pricing is available, but larger-scale needs may lead to higher costs for full support and features.

8. Fivetran

Fivetran is a widely recognized data integration tool known for its ease of use and extensive library of nearly 300 pre-built connectors and an additional 300+ lite (API) connectors. These connectors can be set up in just minutes, streamlining the data integration process. However, it's important to understand Fivetran’s strengths and weaknesses before you decide if it's the right fit for your needs.

Pros:

• Ease of Use: Fivetran is a cloud-native ELT tool with a user-friendly interface that requires minimal coding when setting up data pipelines. 
• Pre-built Connectors: Fivetran offers a wide range of pre-built connectors to various data sources, saving you time and development resources.
• Focus on EL: Fivetran's core strength is data extraction and loading. If what you need mostly is getting information into your warehouse for analysis then it would serve well as an option.

Cons:

• Latency: Fivetran uses batch-based change data capture (CDC), which leads to higher latency when you compare it to streaming CDC solutions. This might not work well if you need to analyze data in real-time.
• Reliability: Some users who use Fivetran have said they've had problems with how reliable it is. They've run into issues like load failures and it takes a long time to fix problems.
• Cost: Fivetran can be higher cost than some other options. Be sure to measure costs for your specific needs first.

Pricing

Fivetran's pricing is based on monthly active rows (MAR), which can be unpredictable due to Fivetran's internal data representation and handling of non-relational sources. Additionally, reducing latency significantly increases costs.

Also Read:

• Estuary vs Fivetran
• Fivetran vs Airbyte
• Fivetran vs Rivery

9. Matillion ETL

Matillion ETL is a reliable data integration tool made for cloud data platforms such as Snowflake, Amazon Redshift, and Google BigQuery. It combines many features to extract, transform, and load (ETL) data.

Pros:

• Cloud-Native Architecture: Matillion ETL runs entirely in your cloud environment, maximizing performance and scalability. This eliminates the need for on-premise infrastructure and simplifies management.
• Flexibility: Matillion ETL supports a variety of transformation options, including visual drag-and-drop components and code editors for complex transformations.
• Pushdown Optimization: Matillion ETL pushes down transformations to the target data warehouse whenever possible. 

Cons:

• Limited Free Tier: Unlike some competitors, Matillion ETL offers a limited free tier with restricted functionality. This can make it challenging to fully evaluate the tool before committing to a paid plan.
• Potential Vendor Lock-in: Matillion ETL's tight integration with specific cloud data platforms might create some vendor lock-in. Switching to a different cloud data warehouse in the future could require rebuilding data pipelines.

10. AWS Glue

AWS Glue steps in as your secret weapon for automating data movement and transformation within the AWS cloud.  This serverless service leverages Apache Spark's power to streamline your data journey, from source to data warehouse, without the trouble of setting up and managing servers.

Pros:

• Serverless Architecture: AWS Glue eliminates the need to provision and manage servers for your ETL jobs. Users only pay for the resources utilized during job execution, which enhances both cost-effectiveness and scalability.
• Pre-built Crawlers and Classifiers: With AWS Glue, data sources are automatically crawled to identify their schema and suggest transformations. This automation minimizes manual configuration efforts, making the development of data pipelines more efficient.
• Integration with AWS Services: AWS Glue works seamlessly with other AWS services like S3, Redshift, and DynamoDB. This facilitates data movement and simplifies building data pipelines within the AWS ecosystem.

Cons:

• Limited Data Source Support: While AWS Glue integrates well with AWS services, it might have limited native support for non-AWS data sources compared to some dedicated ETL tools.
• Cost Optimization: Improperly configured AWS Glue jobs can lead to unexpected costs. Careful monitoring and optimization are crucial for cost-effective use.
• Limited Real-time Capabilities: AWS Glue is primarily designed for batch processing. Real-time data integration might require additional tools or custom development.

11. Hevo Data

Hevo Data is a no-code data pipeline platform. It features a user-friendly GUI-based web application used for constructing and managing data pipelines. This web app functions as the central environment to create, monitor, and manage data flows.

Hevo Data’s generous offering of connectors facilitates seamless integration with a wide variety of data sources and destinations. These combined features render Hevo Data a dynamic solution, adept at handling data integration assignments of diverse scope and complexity

Pros

• It combines the capabilities of ELT, ETL, and Reverse ETL
  
• Automated and codeless data pipelines allow for on-the-fly transformations
  
• Includes robust data governance and security features to safeguard sensitive data
  
• Flexible and scalable platform that caters to small and medium businesses as well as enterprise-level operations

Cons

• Users have reported high CPU usage which can cause system slowdowns
  
• It is a specialized platform with a steep learning curve for some users to fully utilize its features
  
• The inability to schedule a pipeline job for a specific time of the day can limit the platform’s flexibility
  
• Only moves data in near-real-time or batches: no streaming support

Pricing

• Free: Limited to 1 million free events per month with free initial load, 50+ connectors, and unlimited models
  
• Starter ($239/mo): Offers 150+ connectors, on-demand events, and 12 hours of support SLA
  
• Business (Custom Pricing): HIPAA compliance with a dedicated data architect and dedicated account manager

12. SnapLogic

SnapLogic, or SnapLogic Intelligent Integration Platform, is a robust data integration tool with self-service functionality. 

SnapLogic’s browser-based interface comes with 500+ pre-built modifiable connectors called Snaps. It is ideal for any non-technical person in an enterprise to build simple data pipelines. You don’t need to take any help from the IT or data departments for data integration with SnapLogic. Instead, you can use the vendor’s AI assistant, Iris, and the tool’s click-and-go feature for creating robust data pipelines.

Pros

• Runs automatic data quality checks in the background
  
• No technical knowledge is required to integrate a data source into a destination
  
• AI assistant to help integrate platforms
  
• Uses multiple graphs and charts to display ETL job progress

Cons

• Doesn’t provide a lot of customization or code introspections
  
• Focus of the pre-built connectors is only on enterprise SaaS apps

Pricing

Contact their customer support for pricing quotes.

13. Talend

Talend is a data integration and management platform. It offers two products—Talend Data Fabric and Stitch. Talend Data Fabric is a unified platform for reliable and accessible data. And Stitch is a fully-managed data pipeline for analytics.  

However, Talend also has an open-source solution, Talend Open Studio, that can help you kickstart your first data integration and ETL projects. You can use Talend Open Studio for data processes that require lightweight workflows. But, if you’d like to move large amounts of data, requiring massive resources, Talend Open Studio might not be a good choice. 

Pros

• Helpful in building scalable ELT and ETL data pipelines
  
• Capable of both simple and complex transformations
  
• Helps you visualize data pipelines
  
• Over 800+ connectors to help integrate data and business endpoints

Cons

• Several Big Data features are not available in the open-source version
  
• Writing transformations is labor-intensive
  
• Lacks proper documentation 

Pricing

Pricing quotes are available on demand.

14. Dell Boomi

Dell Boomi is a cloud-based integration tool from Dell that helps connect your applications, data, and people to accelerate your digital transformation. It’s an integration platform as a service (iPaaS) that supports on-premise, cloud, or even hybrid architectures.

The Boomi platform is self-managing, self-learning, and self-scaling. It is based on a flexible and scalable runtime layer and offers a complete range of subscribable services. You can select from a large library of pre-built application connectors and integration recipes to jumpstart your integrations. By plugging into Boomi connectors, you can eliminate the time-consuming task of data exchange between applications. For similar functionality, exploring Dell Boomi alternatives may offer better cost-efficiency or additional features.

Pros

• Self-managing, self-learning, and self-scaling
  
• Automation of data transformation 
  
• Provides real-time automatic updates
  
• Supports all-size organizations, from small businesses to enterprises
  
• Supports 180+ software for easy integration with industry-leading software

Cons

• Doesn’t scale well for Big Data or analyics use cases. Boomi is more focused on application integration, not analytics.
  
• Connectors like Excel and CSV files are missing
  
• Advertising SaaS platforms are missing
  
• Lacks parallelization and messaging features for real-time data streaming

Pricing

Customers are charged a monthly subscription fee based on the number of features and connectors used. You can request a quote on the website.

15. ZigiOps

ZigiOps is a flexible, no-code data integration tool that connects various systems swiftly without the need for coding. It’s available in both PaaS and on-premises versions, offering automation of workflows and data synchronization between IT Service Management, Monitoring, DevOps, Cloud, and CRM systems.

With the ZigiOps platform, your organizations can save up to 150K USD per year by automating manual processes. The platform can also reduce the time to resolve issues by 30% through real-time data transfer between teams.

Pros

• With 99.9% uptime, ZigiOps ensures reliable operation
  
• It integrates with over 300 popular systems in various domains
  
• It adheres to best security practices and doesn't store any of your information
  
• The platform offers unlimited scalability which is ideal for growing businesses

Cons

• Limited support is available for Big Data platforms and technologies
  
• Customization options may not be as extensive as some other platforms
  
• Require technical support or consulting services for more complex integrations

Pricing

ZigiOps pricing starts at $800 per month.

16. Jitterbit Harmony

Jitterbit is a cloud integration solution that allows you to connect applications, data, and systems effortlessly. It offers Jitterbit Harmony a low-code integration platform that enables you to create data workflows without writing code. It has pre-built templates that help you quickly move common business processes with the right kind of transformation. 

You can also use its management console to get an overview of all the data integration tasks. So, you can monitor, manage, and control all your data flow tasks from one place. 

Pros

• Suitable for small businesses and large enterprises
  
• Scripting option for extended capabilities in integration

Cons

• Lacks intuitive UI
  
• Higher price than other ETL tools

How To Pick The Best Data Integration Platform: 5 Points To Consider

With so many options to choose from, it can be difficult to decide which data integration solution is right for you. Here are a few things to consider when choosing a data integration platform:

• Connector Library & Integration Capabilities

The platform should have a broad connector library for seamless data extraction from various sources, supporting both cloud-based and on-premise applications and real-time updates.

• Security, Compliance, & Additional Data Services

The tool must adhere to strict security standards, including encryption, access control, and detailed logging. Additional services like big data management and governance can add value.

• Intelligence, Usability, & Support

Choose a user-friendly platform that supports rule-based operations for better data processing speed and accuracy. It should come with strong customer support and extensive documentation.

• Reliability, Speed, & Scalability

Look for a fast, dependable tool capable of reliable data synchronization. It should scale efficiently to meet future data needs with cloud-based options usually offering better scalability.

• Cost Transparency

Understand all costs associated with the tool, including licensing, usage fees, and time costs related to automation, learning, debugging, and maintenance.

Conclusion

The right data integration platform will help you integrate, transform, and move data between various endpoints. However, selecting the best data integration tool based on your requirements is key to streamlining your data flow tasks. Every tool has its advantages and disadvantages. So evaluating its pros and cons thoroughly will help you make the right decision for your organization.

If you want to explore a no-code platform that can help you harness the power of real-time and batch data integration at scale, Estuary Flow could be your perfect match. It provides a unified platform for integrating data from multiple sources and supports a wide range of data formats, including structured, semi-structured, and unstructured data. 

With its real-time capabilities, you can work with up-to-date information and make fast decisions. It's easy to use, flexible, and can connect with existing systems seamlessly.

To benefit from our reliable and user-friendly platform for your data integration needs, sign up now for free or contact our team to discuss your unique requirements.

FAQs

1. What are the benefits of data integration?

Data integration breaks down data silos, allowing you to combine information from various sources for a unified view and deeper insights. This translates to better decision-making and improved business efficiency.

2. What are the different types of data integration tools? 

Different data integration tools include ETL, ELT, streaming, application integration, federated query engines, and data virtualization.

3. Which is the best data integration tool?

The best data integration tool depends on your needs, but Estuary Flow is a strong choice for its support of most data integration patterns. It offers real-time and batch ETL and ELT data integration, supports various data formats, and provides a user-friendly interface for rapid no-code development.

4. What is the difference between Data Integration and Data Ingestion?

Data Ingestion is the process of importing raw data into a system, while Data Integration involves combining, transforming, and loading data from multiple sources for analysis and reporting.

Related blogs:

• Data Streaming Tools
• Change Data Capture Tools
• Cloud ETL Tools
• Data Pipeline Tools
• Data Replication Tools