Best Data Quality Software for Fivetran

Find and compare the best Data Quality software for Fivetran in 2025

Use the comparison tool below to compare the top Data Quality software for Fivetran on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Segment Reviews

    Segment

    Twilio

    $120 per month
    814 Ratings
    See Software
    Learn More
    Twilio Segment’s Customer Data Platform (CDP) provides companies with the data foundation that they need to put their customers at the heart of every decision. Using Twilio Segment, companies can collect, unify and route their customer data into any system. Over 25,000 companies use Twilio Segment to make real-time decisions, accelerate growth and deliver world-class customer experiences.
  • 2
    Mozart Data Reviews
    Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.
  • 3
    DataOps.live Reviews
    Create a scalable architecture that treats data products as first-class citizens. Automate and repurpose data products. Enable compliance and robust data governance. Control the costs of your data products and pipelines for Snowflake. This global pharmaceutical giant's data product teams can benefit from next-generation analytics using self-service data and analytics infrastructure that includes Snowflake and other tools that use a data mesh approach. The DataOps.live platform allows them to organize and benefit from next generation analytics. DataOps is a unique way for development teams to work together around data in order to achieve rapid results and improve customer service. Data warehousing has never been paired with agility. DataOps is able to change all of this. Governance of data assets is crucial, but it can be a barrier to agility. Dataops enables agility and increases governance. DataOps does not refer to technology; it is a way of thinking.
  • 4
    Foundational Reviews
    Identify code issues and optimize code in real-time. Prevent data incidents before deployment. Manage code changes that impact data from the operational database all the way to the dashboard. Data lineage is automated, allowing for analysis of every dependency, from the operational database to the reporting layer. Foundational automates the enforcement of data contracts by analyzing each repository, from upstream to downstream, directly from the source code. Use Foundational to identify and prevent code and data issues. Create controls and guardrails. Foundational can be configured in minutes without requiring any code changes.
  • 5
    Sifflet Reviews
    Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.
  • Previous
  • You're on page 1
  • Next