Struggling to choose between Navicat and Jailer? Both products offer unique advantages, making it a tough decision.
Navicat is a Development solution with tags like database, mysql, mariadb, sql-server, oracle, postgresql, administration, management, visualization, gui.
It boasts features such as Visual database design with drag-and-drop interface, Connect to MySQL, MariaDB, SQL Server, Oracle, PostgreSQL databases, Import, export, synchronize and migrate data between databases and formats, Write, edit, and execute SQL queries, Monitor database connections and performance, Backup and restore databases, Data modeling, reporting and analysis tools and pros including Intuitive graphical user interface, Support for multiple database types, Data migration and synchronization, SQL editor with syntax highlighting, Database administration and maintenance tools, Cross-platform support.
On the other hand, Jailer is a Development product tagged with data-masking, data-anonymization, data-subsetting, database-testing.
Its standout features include Database subsetting, Schema masking, Extracts referentially intact row-sets, Generates data subsets for testing/demos, Masks existing data for sharing, and it shines with pros like Open source, Works with many databases, Simple and easy to use, Good for GDPR compliance, Exports subsets into various formats.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
Navicat is a database administration tool that allows you to visually create, manage, and manipulate databases. It supports MySQL, MariaDB, SQL Server, Oracle, PostgreSQL and more.
Jailer is an open source database subsetting and schema masking tool for relational databases. It extracts consistent, referentially intact row-sets from relational databases and generates data subsets for database tests or demos. It also masks existing data sets for sharing.