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    Show HN: Greenmask 0.2 – Database anonymization tool

    Greenmask

    Dump anonymization and synthetic data generation tool

    Greenmask is a powerful open-source utility that is designed for logical database backup dumping,
    anonymization, synthetic data generation and restoration. It has ported PostgreSQL libraries, making it reliable.
    It is stateless and does not require any changes to your database schema. It is designed to be highly customizable and
    backward-compatible with existing PostgreSQL utilities, fast and reliable.









    Getting started

    Greenmask has a Playground – it is a sandbox environment in Docker with
    sample databases included to help you try Greenmask without any additional actions

    1. Clone the greenmask repository and navigate to its directory by running the following commands:

      git clone git@github.com:GreenmaskIO/greenmask.git && cd greenmask
    2. Once you have cloned the repository, start the environment by running Docker Compose:

      docker-compose run greenmask

    Features

    • Deterministic transformers

      — deterministic approach to data transformation based on the hash
      functions. This ensures that the same input data will always produce the same output data. Almost each transformer
      supports either random or hash engine making it universal for any use case.

    • Dynamic parameters — almost each
      transformer supports dynamic parameters, allowing to parametrize the
      transformer dynamically from the table column value. This is helpful for resolving the functional dependencies
      between columns and satisfying the constraints.
    • Transformation validation and easy maintainable – During
      configuration process, Greenmask provides validation
      warnings, data transformation diff and schema diff features, allowing you to monitor and maintain transformations
      effectively
      throughout the software lifecycle. Schema diff helps to avoid data leakage when schema changed.
    • Partitioned tables transformation inheritance

      — Define transformation configurations once and apply them to all
      partitions within partitioned tables (using apply_for_inherited parameter), simplifying the anonymization process.

    • Stateless – Greenmask operates as a logical dump and does not impact your existing database schema.
    • Cross-platform – Can be easily built and executed on any platform, thanks to its Go-based architecture,
      which eliminates platform dependencies.
    • Database type safe – Ensures data integrity by validating data and utilizing the database driver for
      encoding and decoding operations. This approach guarantees the preservation of data formats.
    • Backward compatible – It fully supports the same features and protocols as existing vanilla PostgreSQL utilities.
      Dumps created by Greenmask can be successfully restored using the pg_restore utility.
    • Extensible – Users have the flexibility
      to implement domain-based transformations
      in any programming language or
      use predefined templates.
    • Integrable – Integrate seamlessly into your CI/CD system for automated database anonymization and
      restoration.
    • Parallel execution – Take advantage of parallel dumping and restoration, significantly reducing the time required
      to deliver results.
    • Provide variety of storages – offers a variety of storage options for local and remote data storage,
      including directories and S3-like storage solutions.
    • Pgzip support for faster compression — by
      setting --pgzip, it can speeds up the dump and restoration
      processes through parallel compression.

    Use Cases

    Greenmask is ideal for various scenarios, including:

    • Backup and Restoration. Use Greenmask for your daily routines involving logical backup dumping and restoration. It
      seamlessly handles tasks like table restoration after truncation. Its functionality closely mirrors that of pg_dump
      and pg_restore, making it a straightforward replacement.
    • Anonymization, Transformation, and Data Masking. Employ Greenmask for anonymizing, transforming, and masking
      backups, especially when setting up a staging environment or for analytical purposes. It simplifies the deployment of
      a pre-production environment with consistently anonymized data, facilitating faster time-to-market in the development
      lifecycle.

    General Information

    It is evident that the most appropriate approach for executing logical backup dumping and restoration is by leveraging
    the core PostgreSQL utilities, specifically pg_dump and pg_restore. Greenmask has been purposefully designed to
    align with PostgreSQL’s native utilities, ensuring compatibility. Greenmask primarily handles data dumping
    operations independently and delegates the responsibilities of schema dumping and restoration to pg_dump and pg_restore,
    maintaining seamless integration with PostgreSQL’s standard tools.

    Backup and Process

    Greenmask uses the directory format of pg_dump and pg_restore. This format is particularly suitable for
    parallel execution and partial restoration, and it includes clear metadata files that aid in determining the backup and
    restoration steps. Greenmask has been optimized to work seamlessly with remote storage systems and anonymization
    procedures.

    Storage Options

    • s3 – This option supports any S3-like storage system, including AWS S3, making it versatile and adaptable to
      various cloud-based storage solutions.
    • directory – This is the standard choice, representing the ordinary filesystem directory for local storage.

    Data Anonymization and Validation

    Greenmask works with COPY lines, collects schema metadata using the Golang driver, and employs this driver in the
    encoding and decoding process. The validate command offers a way to assess the impact on both schema
    (validation warnings) and data (transformation and displaying differences). This command allows you to validate
    the schema and data transformations, ensuring the desired outcomes during the Anonymization process.

    Customization

    If your table schema relies on functional dependencies between columns, you can address this challenge using the
    Dynamic parameters. By setting dynamic
    parameters, you can resolve such as created_at and updated_at cases, where the
    updated_at must be greater or equal than the created_at.

    If you need to implement custom logic imperatively use
    TemplateRecord or
    Template transformers.

    Greenmask provides a framework for creating your custom transformers, which can be reused efficiently. These
    transformers can be seamlessly integrated without requiring recompilation, thanks to the PIPE (stdin/stdout)
    interaction.

    Furthermore, Greenmask’s architecture is designed to be highly extensible, making it possible to introduce other
    interaction protocols, such as HTTP or Socket, for conducting anonymization procedures.

    PostgreSQL Version Compatibility

    Greenmask is compatible with PostgreSQL versions 11 and higher.

    Links

    References

    • Utilized the Demo database, provided by PostgresPro, for integration
      testing purposes.
    • Employed the adventureworks database created
      by morenoh149/postgresDBSamples, in the Docker Compose playground.

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