Compare the Top Data Fabric Software that integrates with Snowflake as of October 2025

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

What is Data Fabric Software for Snowflake?

Data fabric software is a unified data management platform that provides seamless integration, access, and governance across an organization’s entire data ecosystem, regardless of where the data is stored—on-premises, in the cloud, or in hybrid environments. Data fabric software aims to simplify and optimize data integration, management, and analytics by using advanced automation, artificial intelligence (AI), and machine learning (ML) technologies. It helps businesses ensure data consistency, accessibility, and security across multiple data sources, enabling faster and more informed decision-making. By creating a connected data environment, data fabric software improves data quality, accelerates time-to-insight, and enhances overall operational efficiency. Compare and read user reviews of the best Data Fabric software for Snowflake currently available using the table below. This list is updated regularly.

  • 1
    Domo

    Domo

    Domo

    Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results.
  • 2
    Dataddo

    Dataddo

    Dataddo

    Dataddo is a fully-managed, no-code data integration platform that connects cloud-based applications and dashboarding tools, data warehouses, and data lakes. It offers 3 main products: - Data to Dashboards: Send data from apps to dashboarding tools for insights in record time. A free version is available for this product! - Data Anywhere: Send data from apps to warehouses and dashboards, between warehouses, and from warehouses into apps. - Headless Data Integration: Build your own data product on top of the unified Dataddo API. The company’s engineers manage all API changes, proactively monitor and fix pipelines, and build new connectors free of charge in around 10 business days. From first login to complete, automated pipelines, get your data flowing from sources to destinations in just a few clicks.
    Starting Price: $35/source/month
  • 3
    Dagster

    Dagster

    Dagster Labs

    Dagster is a next-generation orchestration platform for the development, production, and observation of data assets. Unlike other data orchestration solutions, Dagster provides you with an end-to-end development lifecycle. Dagster gives you control over your disparate data tools and empowers you to build, test, deploy, run, and iterate on your data pipelines. It makes you and your data teams more productive, your operations more robust, and puts you in complete control of your data processes as you scale. Dagster brings a declarative approach to the engineering of data pipelines. Your team defines the data assets required, quickly assessing their status and resolving any discrepancies. An assets-based model is clearer than a tasks-based one and becomes a unifying abstraction across the whole workflow.
    Starting Price: $0
  • 4
    Microsoft Fabric
    Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.
    Starting Price: $156.334/month/2CU
  • 5
    data.world

    data.world

    data.world

    data.world is a fully managed service, born in the cloud, and optimized for modern data architectures. That means we handle all updates, migrations, and maintenance. Set up is fast and simple with a large and growing ecosystem of pre-built integrations including all of the major cloud data warehouses. When time-to-value is critical, your team needs to solve real business problems, not fight with hard-to-manage data software. data.world makes it easy for everyone, not just the "data people", to get clear, accurate, fast answers to any business question. Our cloud-native data catalog maps your siloed, distributed data to familiar and consistent business concepts, creating a unified body of knowledge anyone can find, understand, and use. In addition to our enterprise product, data.world is home to the world’s largest collaborative open data community. It’s where people team up on everything from social bot detection to award-winning data journalism.
    Starting Price: $12 per month
  • 6
    Avalor

    Avalor

    Avalor

    Avalor’s data fabric helps security teams make faster, more accurate decisions. Our data fabric architecture integrates disparate data sources from legacy systems, data lakes, data warehouses, sql databases, and apps, providing a holistic view of business performance. Automation, 2-way sync, alerts, and analytics live on top of the platform, powered by the data fabric. All security functions benefit from fast, reliable, and precise analysis of enterprise data including asset coverage, compliance reporting, ROSI analysis, vulnerability management, and more. The average security team uses dozens of specialized tools and products, each with its own purpose, taxonomy, and output. With so much disparate data, it’s hard to prioritize your efforts and know exactly where issues lie. Quickly and accurately respond to questions from the business using data from across your organization.
  • 7
    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.
  • 8
    DataBahn

    DataBahn

    DataBahn

    DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 400 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads.
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