Cloud Protectors

AUGMENT NATIVE SECURITY WITH DATA-CENTRIC PROTECTION.

Enforce field-level data protection natively within cloud platforms (AWS, Azure, GCP) & services like Snowflake, Databricks, BigQuery, and S3.
Secure Cloud Innovation

GRANULAR PROTECTION 
WHERE NATIVE CONTROLS END.

Protegrity protects data inside cloud platforms with field-level controls managed centrally, enabling safe, performant analytics and sharing without complex and costly data routing or egress.
Secure Cloud <br>Analytics
Secure Cloud
Analytics
Protect sensitive PII fields in cloud
data warehouses (Snowflake,
BigQuery, Redshift), enabling self-service analytics and reporting
while meeting privacy compliance requirements like GDPR and CCPA
Protect Data <br>Lake Storage
Protect Data
Lake Storage
Apply field-level masking or tokenization directly to sensitive data within cloud object storage (S3, Blob) during ingestion, query, or sharing. Prevent exposure to unauthorized users or partners.
Enforce Compliance <br>In Cloud Databases
Enforce Compliance
In Cloud Databases
Meet data privacy mandates like PCI or HIPAA mandates by encrypting or tokenizing sensitive data directly within cloud-native databases like Redshift, Synapse, RDS, or Azure SQL Database.
Secure Cloud <br>ETL Pipelines
Secure Cloud
ETL Pipelines
Protect sensitive data flowing through cloud data pipelines (using AWS Glue, Azure Data Factory, Google Dataflow) to prevent leakage between services, regions, or environments.
Enable Secure <br>Data Sharing
Enable Secure
Data Sharing
Securely share data stored in cloud platforms like Snowflake or Databricks by protecting sensitive fields while allowing partners or consumers access to non-sensitive data for analysis.
    Key Capabilities

    NATIVE INTEGRATION. BROAD PLATFORM SUPPORT.

    Protegrity provides native integrations and APIs that allow you to apply consistent, field-level protection across diverse cloud services, databases, data lakes, and data pipelines.

    Media block image

    Native Platform Integration

    Apply protection directly within the runtime of major cloud data platforms (Snowflake, Databricks, BigQuery, Redshift), ensuring security without requiring data movement or external proxies

    • Seamless, high-performance integration with leading cloud data services
    • Protection applied transparently during query execution or pipeline processing
    • Maintains platform compatibility with existing analytics and AI/ML workflows
    Media block image

    Broad Cloud
    Service Coverage

    Extend consistent protection beyond databases—including data lakes (S3, Blob, GCS), object storage, and critical data pipeline services across AWS, Azure, and GCP.

    • Comprehensive support for major cloud providers and their key data services
    • Includes protection for Hadoop ecosystems (Hive, Spark) running in the cloud
    • Protect data within ETL/ELT services (Glue, Data Factory, Dataflow) via Cloud API
    Media block image

    Field-Level
    Protection Methods

    Precisely enforce data protection policies, applying granular vaultless tokenization, encryption, masking, or anonymization to specific sensitive data fields within cloud environments.

    • Protect PII, PCI, PHI, and other sensitive data types at the column or field level
    • Protection methods operate transparently to users during query or data access
    • Format-preserving options (i.e., dynamic data masking) maintain usability for downstream analytics and AI tools
    Media block image

    Centralized Policy Enforcement

    Ensure consistent application of enterprise-wide data protection rules. Policies are defined centrally in the Protegrity Enterprise Security Administrator (ESA) but applied locally by the Application Protector within the app context.

    • All app-specific policies managed centrally via Protegrity ESA for consistency and simplified admin
    • Local enforcement ensures security rules are always applied correctly in context
    • Enables granular, policy-based control over who sees clear vs. protected data
    Where Does Your Sensitive Data Live?

    APPLY PRIVACY PRESERVATION ANYWHERE IN YOUR ARCHITECTURE.

    Protegrity’s field-level, format-preserving privacy preservation methods can be applied consistently via various mechanisms—Protegrity Protectors—embedded across your data environment. Select the enforcement point(s) that best fits your architecture and specific use case needs.
    Cloud
    environments
    Secure dynamic, cloud-native workloads.
    Applications
    Protect data as it moves through your stack.
    Saas
    Platforms
    Secure third-party tools.
    Data
    Stores
    Protect structured data at rest or in motion.
    Core
    systems
    Add modern security to legacy or mainframe systems.

      View an
      Online Demo

      Accelerate data access and turn data security into a competitive advantage with Protegrity’s uniquely data-centric approach to data protection.

      THE LATEST
      FROM PROTEGRITY

      Enterprise Data Security
      In A Single Platform

      Equip teams to discover, govern, and protect sensitive data across the
      data lifecycle—including for analytics and AI.

      Discovery

      Identify sensitive data (PII, PHI, PCI, IP) across structured and unstructured sources using ML and rule-based classification.

      Learn More

      Governance

      Define and manage access and protection policies based on role, region, or data type—centrally enforced and audited across systems.

      Learn more

      Protection

      Apply field-level protection methods—like tokenization, encryption, or masking—through enforcement points such as native integrations, proxies, or SDKs.

      Learn more

      Privacy

      Support analytics and AI by removing or transforming identifiers using anonymization, pseudonymization, or synthetic data generation—balancing privacy with utility.

      Learn more