Best Data Classification Software for Snowflake

Find and compare the best Data Classification software for Snowflake in 2025

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

  • 1
    MineOS Reviews
    MineOS is a UX-focused data privacy platform that knows compliance work has been rough in the past. Our automated no-code platform can be up & running in a day to bring companies comprehensive data mapping & classification that integrates with hundreds of popular data sources and discovers nearly 100% of a company’s data. By mapping and classifying data better, DSR management, risk assessments, and data policy enforcement all become easier and faster. Simplify compliance. Gain consumer trust. MineOS.ai
  • 2
    Dasera Reviews

    Dasera

    Dasera

    3 data stores at $20,000
    Dasera is a Data Security Posture Management (DSPM) solution that provides comprehensive security and governance for structured and unstructured data across cloud and on-premises environments. It uniquely monitors data-in-use, offering continuous visibility and automated remediation to prevent data breaches at every data lifecycle stage. Dasera facilitates continuous risk detection and mitigation, ensuring seamless integration and regulation compliance. With a deep understanding of data infrastructure, attributes, users, and usage, Dasera empowers organizations to pursue a secure, data-driven growth strategy, minimizing risks and maximizing value in the digital era.
  • 3
    Protegrity Reviews
    Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.
  • 4
    Mage Sensitive Data Discovery Reviews
    Mage Sensitive Data Discovery module can help you uncover hidden data locations in your company. You can find data hidden in any type of data store, whether it is structured, unstructured or Big Data. Natural Language Processing and Artificial Intelligence can be used to find data in the most difficult of places. A patented approach to data discovery ensures efficient identification of sensitive data and minimal false positives. You can add data classifications to your existing 70+ data classifications that cover all popular PII/PHI data. A simplified discovery process allows you to schedule sample, full, and even incremental scans.
  • 5
    Nightfall Reviews
    Uncover, categorize, and safeguard your sensitive information with Nightfall™, which leverages machine learning technology to detect essential business data, such as customer Personally Identifiable Information (PII), across your SaaS platforms, APIs, and data systems, enabling effective management and protection. With the ability to integrate quickly through APIs, you can monitor your data effortlessly without the need for agents. Nightfall’s machine learning capabilities ensure precise classification of sensitive data and PII, ensuring comprehensive coverage. You can set up automated processes for actions like quarantining, deleting, and alerting, which enhances efficiency and bolsters your business’s security. Nightfall seamlessly connects with all your SaaS applications and data infrastructure. Begin utilizing Nightfall’s APIs for free to achieve sensitive data classification and protection. Through the REST API, you can retrieve organized results from Nightfall’s advanced deep learning detectors, identifying elements such as credit card numbers and API keys, all with minimal coding. This allows for a smooth integration of data classification into your applications and workflows utilizing Nightfall's REST API, setting a foundation for robust data governance. By employing Nightfall, you not only protect your data but also empower your organization with enhanced compliance capabilities.
  • 6
    Adaptive Reviews
    Adaptive is a sophisticated data security solution aimed at safeguarding sensitive information from being exposed to both human and automated entities. It boasts a secure control plane that allows for data protection and access, utilizing an agentless framework that eliminates the need for network reconfiguration and can be implemented in either cloud environments or on-premises settings. This platform empowers organizations to grant privileged access to data resources without the necessity of sharing actual credentials, thereby bolstering their security measures. Additionally, it offers just-in-time access to a variety of data sources such as databases, cloud infrastructure, data warehouses, and web services. Furthermore, Adaptive streamlines non-human data interactions by linking third-party tools or ETL pipelines through a centralized interface, ensuring that data source credentials remain confidential. To reduce the risk of data exposure, the platform incorporates data masking and tokenization for users without privileged access, all while maintaining existing access workflows. Moreover, it ensures thorough audibility through identity-based audit trails that encompass all resources, allowing organizations to monitor and track access effectively. In this way, Adaptive establishes a robust framework for data security and management in modern digital ecosystems.
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