Best Data Migration Software for Azure DevOps Projects

Compare the Top Data Migration Software that integrates with Azure DevOps Projects as of June 2025

This a list of Data Migration software that integrates with Azure DevOps Projects. Use the filters on the left to add additional filters for products that have integrations with Azure DevOps Projects. View the products that work with Azure DevOps Projects in the table below.

What is Data Migration Software for Azure DevOps Projects?

Data migration software enables the seamless migration of data from one system or another. Data migration tools are useful for database migration, application migration, server migration, data center migration, and more. Compare and read user reviews of the best Data Migration software for Azure DevOps Projects currently available using the table below. This list is updated regularly.

  • 1
    StarfishETL

    StarfishETL

    StarfishETL

    StarfishETL is an Integration Platform as a Service (iPaaS), and although “integration” is in the name, it’s capable of much more. An iPaaS lives in the cloud and can integrate different systems by using their APIs. This makes it adaptable beyond integration for migration, data governance, and data cleansing. Unlike traditional integration apps, StarfishETL provides low-code mapping and powerful scripting tools to manage, personalize, and manipulate data at scale. Features: - Drag and drop mapping - AI-powered connections - Purpose built integrations - Extensibility through scripting - Secure on-premises connections - Scalable data capacity
    Starting Price: 400/month
  • 2
    IRI Voracity

    IRI Voracity

    IRI, The CoSort Company

    Voracity is the only high-performance, all-in-one data management platform accelerating AND consolidating the key activities of data discovery, integration, migration, governance, and analytics. Voracity helps you control your data in every stage of the lifecycle, and extract maximum value from it. Only in Voracity can you: 1) CLASSIFY, profile and diagram enterprise data sources 2) Speed or LEAVE legacy sort and ETL tools 3) MIGRATE data to modernize and WRANGLE data to analyze 4) FIND PII everywhere and consistently MASK it for referential integrity 5) Score re-ID risk and ANONYMIZE quasi-identifiers 6) Create and manage DB subsets or intelligently synthesize TEST data 7) Package, protect and provision BIG data 8) Validate, scrub, enrich and unify data to improve its QUALITY 9) Manage metadata and MASTER data. Use Voracity to comply with data privacy laws, de-muck and govern the data lake, improve the reliability of your analytics, and create safe, smart test data
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