Compare the Top Data Mapping Software in Asia as of February 2026

What is Data Mapping Software in Asia?

Data mapping software enables users to accurately map data points so that source fields and destination fields are mapped correctly. Data mapping tools are useful for data migrations, data integrations, or data transformations. Compare and read user reviews of the best Data Mapping software in Asia currently available using the table below. This list is updated regularly.

  • 1
    MANTA

    MANTA

    Manta

    Manta is the world-class automated approach to visualize, optimize, and modernize how data moves through your organization through code-level lineage. By automatically scanning your data environment with the power of 50+ out-of-the-box scanners, Manta builds a powerful map of all data pipelines to drive efficiency and productivity. Visit manta.io to learn more. With Manta platform, you can make your data a truly enterprise-wide asset, bridge the understanding gap, enable self-service, and easily: • Increase productivity • Accelerate development • Shorten time-to-market • Reduce costs and manual effort • Run instant and accurate root cause and impact analyses • Scope and perform effective cloud migrations • Improve data governance and regulatory compliance (GDPR, CCPA, HIPAA, and more) • Increase data quality • Enhance data privacy and data security
  • 2
    Aggua

    Aggua

    Aggua

    Aggua is a data fabric augmented AI platform that enables data and business teams Access to their data, creating Trust and giving practical Data Insights, for a more holistic, data-centric decision-making. Instead of wondering what is going on underneath the hood of your organization's data stack, become immediately informed with a few clicks. Get access to data cost insights, data lineage and documentation without needing to take time out of your data engineer's workday. Instead of spending a lot of time tracing what a data type change will break in your data pipelines, tables and infrastructure, with automated lineage, your data architects and engineers can spend less time manually going through logs and DAGs and more time actually making the changes to infrastructure.
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