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Jailer 16.5
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license: Open Source
downloads: 97
size: 75.70 MB
updated: 2024-10-06
tags: Jailer, download Jailer, Jailer free download, data extractor, export database, import data, extract, subset, sample, extractor
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Ralf Wisser
"Jailer" is a sophisticated data management tool meticulously crafted by Ralf Wisser, designed to streamline and enhance the process of database subsetting and data extraction. This open-source software stands out for its robust capabilities in managing large datasets, making it an indispensable asset for database administrators, developers, and data analysts.
At its core, Jailer excels in creating consistent and referentially intact subsets of relational data. This is particularly useful for tasks such as testing, development, and data warehousing, where working with a full production database is impractical. By extracting only the relevant portions of data, Jailer ensures that the subsets maintain the integrity and relationships of the original dataset, thereby preserving the context and usability of the data.
One of the standout features of Jailer is its intuitive and user-friendly interface, which simplifies the complex process of data extraction. Users can define extraction rules through a graphical interface, making it accessible even to those with limited SQL knowledge. The software supports a wide range of databases, including Oracle, MySQL, PostgreSQL, and SQL Server, ensuring versatility and broad applicability across different database environments.
Jailer also offers powerful data anonymization capabilities, which are crucial for maintaining data privacy and compliance with regulations such as GDPR. By anonymizing sensitive information, Jailer allows organizations to use real data in non-production environments without compromising privacy.
Another notable feature is Jailer's ability to handle complex data models with ease. It can navigate intricate relationships and dependencies within the data, ensuring that all necessary related records are included in the subset. This thorough approach minimizes the risk of missing critical data and enhances the reliability of the extracted subsets.
Performance-wise, Jailer is optimized to handle large volumes of data efficiently. Its advanced algorithms and optimization techniques ensure that the extraction process is both fast and resource-efficient, making it suitable for use in environments with substantial data loads.
In addition to its core functionalities, Jailer offers a range of supplementary tools and features, such as data visualization and analysis capabilities, which provide deeper insights into the data and facilitate better decision-making. The software's extensibility through plugins and custom scripts further enhances its adaptability to specific use cases and requirements.
Overall, Jailer by Ralf Wisser is a powerful, versatile, and user-friendly data management tool that excels in database subsetting and data extraction. Its combination of robust features, performance optimization, and ease of use makes it a valuable addition to any data professional's toolkit. Whether you're looking to streamline your testing processes, ensure data privacy, or manage complex data models, Jailer provides a comprehensive solution that delivers consistent and reliable results.
At its core, Jailer excels in creating consistent and referentially intact subsets of relational data. This is particularly useful for tasks such as testing, development, and data warehousing, where working with a full production database is impractical. By extracting only the relevant portions of data, Jailer ensures that the subsets maintain the integrity and relationships of the original dataset, thereby preserving the context and usability of the data.
One of the standout features of Jailer is its intuitive and user-friendly interface, which simplifies the complex process of data extraction. Users can define extraction rules through a graphical interface, making it accessible even to those with limited SQL knowledge. The software supports a wide range of databases, including Oracle, MySQL, PostgreSQL, and SQL Server, ensuring versatility and broad applicability across different database environments.
Jailer also offers powerful data anonymization capabilities, which are crucial for maintaining data privacy and compliance with regulations such as GDPR. By anonymizing sensitive information, Jailer allows organizations to use real data in non-production environments without compromising privacy.
Another notable feature is Jailer's ability to handle complex data models with ease. It can navigate intricate relationships and dependencies within the data, ensuring that all necessary related records are included in the subset. This thorough approach minimizes the risk of missing critical data and enhances the reliability of the extracted subsets.
Performance-wise, Jailer is optimized to handle large volumes of data efficiently. Its advanced algorithms and optimization techniques ensure that the extraction process is both fast and resource-efficient, making it suitable for use in environments with substantial data loads.
In addition to its core functionalities, Jailer offers a range of supplementary tools and features, such as data visualization and analysis capabilities, which provide deeper insights into the data and facilitate better decision-making. The software's extensibility through plugins and custom scripts further enhances its adaptability to specific use cases and requirements.
Overall, Jailer by Ralf Wisser is a powerful, versatile, and user-friendly data management tool that excels in database subsetting and data extraction. Its combination of robust features, performance optimization, and ease of use makes it a valuable addition to any data professional's toolkit. Whether you're looking to streamline your testing processes, ensure data privacy, or manage complex data models, Jailer provides a comprehensive solution that delivers consistent and reliable results.
OS: Windows 11, Windows 10 32/64 bit, Windows Server 2012 R2, Windows Server 2012, Windows 2008 R2, Windows 8 32/64 bit, Windows 7 32/64 bit, Windows Vista
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