13 Best Data Migration Tools for Moving Data in 2025

Choosing the right data migration tool is critical to any successful cloud, CRM, or enterprise modernization initiative. Whether you're consolidating systems, moving to a cloud data warehouse, or upgrading platforms, the tool you choose directly impacts speed, reliability, and risk. However, finding the perfect solution for your business can be downright intimidating, especially when a simple Google search sends you down a never-ending rabbit hole.

We’re here to help clear things up.

In this guide, we’ll break down the best data migration tools and software available in 2025, focusing on key features to look for and how Matillion compares to other leading options. From cloud-native powerhouses to user-friendly platforms for non-technical teams, in your search for data migration software, we've got you covered.

What Is a Data Migration Tool?

A data migration tool helps you move data from one system, storage location, or format to another. The process may involve:

• Moving from on-premise databases to the cloud (e.g. SQL Server to Snowflake)
• Migrating CRM platforms (e.g. Salesforce to HubSpot)
• Consolidating legacy systems
• Replatforming or modernizing data infrastructure

However, today's tools do much more than simply shuttle bits and bytes around. They're comprehensive platforms that handle every aspect of the migration process in order to reduce risk and ensure consistency across environments:

• Data extraction: They identify and collect data from source systems—whether it's a legacy database, a cloud storage solution, or a mishmash of spreadsheets scattered across your organization.
• Data transformation: Raw data often needs a cleanup before it can settle into its new home. Migration tools can clean, format, and restructure data to guarantee it fits into the target system.
• Data loading: Once your data is prepped and ready, these tools safely deposit it into its new location, whether that's a sleek cloud data warehouse or a state-of-the-art on-premises system.
• Validation and testing: Good migration tools include features to verify that your data arrived intact and functions as expected in its new environment.
• Scheduling and automation: Many tools offer scheduling capabilities to automate recurring migrations.
• Security and compliance: Migration tools often include encryption, access controls, and audit trails to keep your data safe and your operations compliant.
• Error handling and logging: When things go sideways (and in the world of data, they sometimes do), migration tools provide detailed logs and error-handling mechanisms to help you quickly identify and resolve issues.

Does Your Business Need a Data Migration Tool?

Whether you're consolidating databases after a merger, upgrading to a new CRM system, or making the leap to a cloud-based infrastructure, a data migration tool makes it all possible. If you answer “yes” to any of the following scenarios, then you could probably use a data migration tool:

• You're drowning in spreadsheets: If your critical business data is scattered across countless Excel files, CSV dumps, and maybe even a few dusty filing cabinets, it's time for a change.
• Your legacy systems are showing their age: That database from the '90s might have served you well, but it's holding you back from leveraging modern analytics and cloud capabilities.
• You're going through a merger or acquisition: Combining two (or more) companies' worth of data without the right tools is asking for major problems.
• Cloud migration is on your roadmap: Moving to the cloud isn't just a lift-and-shift operation. You need a tool that can handle the nuances of cloud data architectures.
• You're upgrading critical business systems: Whether it's a new CRM, ERP, or any other acronym-heavy software, data migration is the make-or-break factor in a successful rollout.
• Your data quality is questionable at best: If you can't trust your data, you can't trust your decisions. A good migration tool can help clean and standardize your information.
• Manual data entry is eating up valuable time: Your team's talents are wasted on copy-paste marathons. Automation frees up resources for higher-value work.
• You're eyeing advanced analytics or AI projects: These initiatives are only as good as the data that feeds them. A migration tool can help guarantee your data is ready for action.
• Scalability is becoming an issue: As your business grows, so does your data. You need a solution that can handle increasing volumes without breaking down.

Remember, data migration isn't just about moving information from point A to point B. It's about setting your business up for future success. A good data migration tool doesn't just solve immediate challenges—it opens up new possibilities for innovation, efficiency, and growth.

Factors to Consider When Choosing a Data Migration Software

Choosing the right data migration software is easier said than done, and it’s easy for information overload to slow down your decision-making process. Here are the factors you need to look at to cut through the noise and get down to what really matters:

• Compatibility and connectivity: First things first—can the tool actually talk to your systems? Look for broad support of data sources and destinations, including databases, cloud services, and file formats. The more native connectors a tool offers, the less custom coding you'll need to wrangle.
• Scalability: Your data needs today might be manageable, but what about next year? Or in five years? Choose a tool that can grow with your business.
• Performance: Time is money, and in the world of data migration, slow performance can be costly. Look for tools with optimized processing engines, parallel execution capabilities, and efficient data handling mechanisms.
• Data transformation capabilities: Robust transformation features can save you countless hours of post-migration cleanup.
• Ease of use: Look for intuitive interfaces, visual mapping tools, and clear documentation.
• Security and compliance: Check for security features like encryption, access controls, and audit trails. If you're in a regulated industry, compliance support is non-negotiable.
• Error handling and validation: Things rarely go perfectly in the world of data. A good migration tool should have error handling, data validation, and reconciliation features to catch issues before they become problems.
• Automation capabilities: The less manual intervention required, the better. Look for tools that offer scheduling, workflow automation, and the ability to create reusable migration templates.
• Cloud-readiness: Even if you're not in the cloud now, you probably will be soon. Choose a tool that's built for modern, cloud-native environments and can handle hybrid scenarios.
• Cost and ROI: While price shouldn't be your only consideration, it's still important. Look beyond the sticker price to consider total cost of ownership, including training, support, and potential productivity gains.

Remember, the "best" tool isn't necessarily the one with the most features or the highest price tag. It's the one that best aligns with your specific business needs, technical capabilities, and growth trajectory.

13 Best Data Migration Tools in 2025

1. Matillion

Matillion is a cloud-native data integration and transformation platform that helps businesses unlock the power of their data. It's built for cloud data warehouses and provides a user-friendly interface for both technical and non-technical users. Matillion leverages the scalability and performance of cloud platforms to let businesses transform large volumes of data quickly and efficiently. Its low-code/no-code approach democratizes data integration.

Matillion have unveiled Maia, a team of agentic data engineers available exclusively within the Data Productivity Cloud. Whether you're building, testing, or analyzing – collaborate with Maia to accelerate pipeline development, automate repetitive tasks, and keep data flowing cleanly. What sets Matillion apart is its ability to leverage the scalability and performance of cloud platforms to enable businesses to transform large volumes of data quickly and efficiently.

Key features include:

• Maia, Agentic Data Engineers: Supercharge all aspects of data engineering with Maia, the purpose-built AI data workforce.
• Cloud-native architecture: Optimized for leading cloud data platforms like Snowflake, Amazon Redshift, and Google BigQuery.
• Visual ETL/ELT designer: Intuitive drag-and-drop interface for building data workflows, reducing the need for extensive coding skills.
• Pushdown optimization: Leverages the processing power of your cloud data warehouse for improved performance and reduced data movement.
• Comprehensive connector library: Wide range of pre-built connectors for popular data sources and destinations.
• Data quality and governance tools: Built-in features for maintaining data integrity and compliance throughout the migration process.
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2. AWS Database Migration Service (DMS)

AWS Database Migration Service is a cloud-based service designed to help businesses migrate databases to AWS quickly. It supports both homogeneous migrations (such as Oracle to Oracle) and heterogeneous migrations (such as Oracle to Amazon Aurora). It does all this with minimal downtime, allowing source databases to remain fully operational during the migration process. It's also deeply integrated with other AWS services, making it a great fit for businesses already invested in the AWS ecosystem.

Key features include:

• Continuous data replication: Supports ongoing replication for use cases like disaster recovery and data consolidation (in addition to one-time migrations).
• Wide database support: Compatible with most popular commercial and open-source databases, both as sources and targets.
• Schema conversion tool: Automatically converts source database schema and code to match the target database to simplify heterogeneous migrations.
• AWS integration: Works with other AWS services like Amazon S3, Amazon Redshift, and Amazon Aurora for comprehensive data management solutions.
• Minimal downtime: Uses change data capture (CDC) to keep source and target databases in sync during migration.

3. Fivetran

Fivetran is a cloud-native, fully managed data integration platform that automates the extract and load processes of ELT (Extract, Load, Transform). It provides "zero-maintenance pipelines" to simplify data migration by handling the complexities of data extraction and loading with minimal user intervention. Fivetran can adapt to schema changes automatically to help businesses with evolving data structures.

Key features include:

• Automated schema management: Automatically detects and adapts to changes in source data schemas to reduce pipeline breakages and maintenance overhead.
• Extensive connector library: Offers a wide range of pre-built, fully managed connectors for popular data sources and SaaS applications.
• Incremental updates: Syncs data by updating only what has changed since the last sync, minimizing data transfer and associated costs.
• Integrated dbt transformation: Fivetran supports in-warehouse transformations via dbt integration, ensuring data is ready for analysis without requiring a separate processing framework.
• Real-time monitoring and alerts: Provides proactive notifications about pipeline status and potential issues to maintain data reliability and freshness.

4. Stitch

Qlik Stitch is a cloud-first, developer-focused data integration platform that specializes in extracting and loading data from various sources into data warehouses and data lakes. It uses an ETL (Extract, Transform, Load) approach to move data into a centralized location where it can be transformed as needed. Stitch sets itself apart with its simplicity and speed of setup, often allowing users to configure data pipelines in minutes rather than days or weeks. Its open-source roots and support for the Singer specification make it highly extensible for developers who need to create custom integrations.

Key features include:

• Rapid setup: User-friendly interface allows for quick configuration of data pipelines with minimal technical expertise required.
• Extensive source integrations: Offers a wide range of pre-built connectors for popular databases, SaaS applications, and analytics tools.
• Singer integration: Supports the open-source Singer specification for writing scripts for uncommon data sources.
• Automatic schema detection: Identifies and adapts to changes in source data structures to reduce maintenance overhead and pipeline failures.
• Usage-based pricing: Transparent, consumption-based pricing model that scales with your data volume makes it accessible for businesses of all sizes.

5. Talend

Talend is a comprehensive data integration and integrity platform with solutions for data integration, quality, governance, and cataloging. It provides both on-premises and cloud-based options. Talend takes a unified approach to data management, combining robust ETL capabilities with data quality and governance features in a single suite. Its open-source foundations and extensive community support make it a great choice for businesses that need flexibility and customization.

Key features include:

• Unified platform: Integrates data management, data quality, and application integration in a single suite.
• Data preparation tools: Offers self-service features for business users to explore, cleanse, and prepare data for analysis.
• Machine learning capabilities: Incorporates AI and machine learning for smart data quality and matching functions.
• Extensive connectivity: Supports a range of data sources and destinations, including on-premises systems, cloud services, and big data platforms.
• Real-time and batch processing: Capable of handling both real-time data integration and batch processing.

6. Snowflake Snowpipe

Snowflake Snowpipe is a cloud-native, serverless data ingestion service designed for Snowflake's data cloud platform. It enables continuous, incremental data loading into Snowflake for near real-time data availability. Snowpipe provides a seamless integration with Snowflake's ecosystem and automatically ingests data as soon as it lands in a staging area. This makes it a great fit for businesses that need to maintain up-to-the-minute data accuracy in their Snowflake environment without managing complex ETL processes or schedules.

Key features include:

• Automated data ingestion: Continuously loads new data into Snowflake tables as soon as it arrives in a designated staging area.
• Serverless architecture: Automatically scales resources based on ingestion needs, removing the burden of infrastructure management and optimizing costs.
• File format support: Handles various file formats including CSV, JSON, Avro, and Parquet.
• Data transformation: Supports basic transformations during ingestion to allow for data preprocessing before it reaches the target table.
• Integration with cloud storage: Works with major cloud storage providers like AWS S3, Azure Blob Storage, and Google Cloud Storage.

7. Airbyte

Airbyte is an open core data integration platform. It's designed to address the long tail of integrations to allow users to build and contribute their own connectors. Airbyte provides a modern, API-first architecture that’s committed to transparency and collaboration. With both cloud and self-hosted options available, Airbyte offers flexibility in deployment and data control.

Key features include:

• Open-source core: Provides full visibility into the codebase and allows for customization to meet specific business needs.
• Extensive connector library: Offers a growing list of pre-built connectors with new ones regularly added by the community.
• No-code configuration: User-friendly interface for setting up and managing data pipelines without coding.
• Data normalization: Optional post-load normalization of data to simplify downstream analytics for consistency across different data sources.
• Flexible deployment: Supports both cloud and self-hosted deployments to give businesses control over their data and infrastructure.

8. Informatica

Informatica is a leader in enterprise cloud data management. It offers a comprehensive suite of data integration tools tailor-made for large-scale, complex data environments. Its Intelligent Data Management Cloud (IDMC) platform provides end-to-end capabilities for data integration, quality, governance, and cataloging. Informatica takes an AI-driven automation approach to improve various aspects of data management. Informatica's robust enterprise-grade features and scalability make it popular among large organizations with complex data ecosystems.

Key features include:

• AI-powered automation: The CLAIRE AI engine automates and optimizes various data management tasks.
• Multi-cloud, hybrid support: Offers flexible deployment options across on-premises, cloud, and hybrid environments.
• Metadata-driven intelligence: Leverages metadata to provide insights, automate data discovery, and improve data lineage tracking, enhancing overall data governance.
• Advanced data quality tools: Comprehensive suite for profiling, cleansing, and standardizing data across the enterprise, ensuring data reliability and consistency.
• Extensive connectivity: Wide range of pre-built connectors for databases, applications, and cloud services to support complex integration scenarios in varied IT landscapes.

9. Azure Migrate

Azure Migrate is Microsoft's comprehensive platform for evaluating, planning, and executing migrations to Azure cloud services. While it's not exclusively a data migration tool, it facilitates database and workload migrations as part of broader cloud adoption strategies. Azure Migrate provides integrated tools for discovery, assessment, and migration of servers, databases, and applications.

Key features include:

• Unified migration platform: Provides a centralized hub for planning and executing migrations of servers, databases, web apps, and virtual desktops to Azure.
• Comprehensive discovery and assessment: Offers tools to inventory on-premises resources, assess readiness, and estimate costs for Azure migration.
• Database migration support: Includes Azure Database Migration Service for migrating various database types to Azure database services with minimal downtime.
• Agentless dependency mapping: Visualizes dependencies between servers and applications without requiring agents.
• Integration with Azure services: Works easily with other Azure tools and services.

10. Pentaho Data Integration

Pentaho Data Integration is an open-source ETL (Extract, Transform, Load) tool that's part of the larger Pentaho suite of business intelligence and data integration tools. It provides a powerful and flexible platform for designing and executing data workflows. Pentaho’s visual design environment (combined with the ability to extend functionality through custom scripting) offers both ease-of-use and advanced capabilities.

Key features include:

• Visual ETL designer: Intuitive drag-and-drop interface for creating data integration workflows.
• Extensive connectivity: Supports a wide range of data sources and destinations, including databases, flat files, cloud services, and big data platforms.
• Transformation library: Offers a rich set of pre-built transformations and job steps to accelerate the development of data integration processes.
• Metadata injection: Allows for dynamic ETL job generation for more flexible and reusable data integration solutions.
• Clustering and partitioning: Supports distributed processing for handling large volumes of data efficiently.

11. Precisely Connect

Precisely Connect (formerly Syncsort DMX-h) is a data integration platform that handles high-volume, complex data integration scenarios across diverse environments. It specializes in connecting legacy systems with modern data platforms, making it particularly valuable for organizations with a mix of traditional and cutting-edge data infrastructure. Precisely Connect can process massive data volumes efficiently. It follows the design philosophy of "design once, deploy anywhere," which allows for flexible deployment across various environments.

Key features include:

• High-performance engine: Optimized for processing large volumes of data quickly with the ability to handle both batch and real-time data integration scenarios.
• Mainframe connectivity: Offers strong support for integrating mainframe data with modern data platforms.
• Change data capture (CDC): Enables real-time data replication by capturing and propagating only the changes made to source systems.
• Data quality and profiling: Includes built-in data quality and profiling capabilities to maintain the accuracy and consistency of data throughout the integration process.
• Flexible deployment: Supports on-premises, cloud, and hybrid deployments.

12. IBM InfoSphere DataStage

IBM InfoSphere DataStage is a powerful data integration platform that's part of IBM's broader InfoSphere suite. It helps organizations understand, cleanse, transform, and deliver trusted information to business initiatives. InfoSphere DataStage provides enterprise-grade scalability, robust data governance capabilities, and deep integration with IBM's ecosystem of data management tools. It's well-suited for large organizations with complex data environments and those already invested in IBM technologies.

Key features include:

• Parallel processing framework: Enables high-performance data integration by distributing processing across multiple nodes.
• Extensive connectivity: Supports a wide range of data sources and targets, including traditional databases, big data platforms, and cloud services.
• Built-in data quality tools: Incorporates data cleansing and standardization capabilities to maintain data integrity throughout the integration process.
• Metadata management: Offers comprehensive metadata tracking and lineage capabilities.
• Designer client: Provides a graphical interface for designing complex data integration jobs to balance ease of use with powerful functionality for advanced users.

13. CloverDX

CloverDX is a flexible data integration platform that handles complex data transformations and migrations. It provides a unique blend of visual design and code-based development that make it usable for both citizen integrators and experienced developers. CloverDX seamlessly scales from simple data tasks to enterprise-grade data operations, focusing on data accuracy and consistency throughout the integration process. Its modular architecture allows for easy customization and extension, making it adaptable to a range of data integration scenarios.

Key features include:

• Hybrid visual/code development: Provides both a graphical interface for designing data flows and the ability to dive into code for more complex transformations.
• Data profiling and cleansing: Offers built-in tools for analyzing data quality and performing data cleansing operations.
• Jobflow orchestration: Allows for the creation of complex data workflows, combining multiple transformations and integrations into cohesive, manageable processes.
• Automated testing and debugging: Includes features for unit testing and debugging data transformations.
• Metadata management: Provides strong metadata handling capabilities to improve data lineage tracking and overall data governance.

Data Integration Tools Comparison

Why Choose Matillion for Data Migration?

Matillion is purpose-built for modern cloud data stacks. Whether you're migrating from legacy systems or consolidating cloud apps, Matillion makes the process easier and faster with:

• Agentic AI, built in, Maia is only available within the Data Productivity Cloud
• Native connectors to Snowflake, Databricks, Redshift, BigQuery, and more
• Orchestration workflows that automate end-to-end migration steps
• Support for semi-structured data like JSON, Parquet, and XML
• Scalable performance to handle complex, large-volume enterprise data
• Low-code UI and full API support for developer-friendly integrations

Key Features Summary

Move Your Data Reliably at Scale with Matillion

While there are plenty of data migration tools for you to choose from, we believe (unbiasedly, of course) that Matillion is the best for businesses looking to unlock the full potential of their cloud data. 

Matillion isn’t just about raw power. Its intuitive, low-code interface democratizes data integration, allowing teams across your organization to collaborate effectively on data projects. From seasoned data engineers to business analysts taking their first steps into the world of data, Matillion provides the tools to turn raw information into actionable insights.

Try it for yourself. Start your 14-day free trial to see how Matillion can streamline your data migration processes.