Best SQL Databases for FastReport Mono

Find and compare the best SQL Databases for FastReport Mono in 2024

Use the comparison tool below to compare the top SQL Databases for FastReport Mono on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    MySQL Reviews
    MySQL is the most widely used open-source database in the world. MySQL is the most popular open source database for web-based applications. It has been proven to be reliable, performant, and easy-to-use. This database is used by many high-profile web properties, including Facebook, Twitter and YouTube. It is also a popular choice for embedded databases, distributed by thousands ISVs and OEMs.
  • 2
    SQLite Reviews
    Top Pick
    SQLite is a C language library that implements a small, fast and self-contained SQL database engine. It is highly reliable, compact, efficient, and fully-featured. SQLite is the most widely used database engine in the globe. SQLite is embedded in all mobile phones and computers. It also comes with countless other applications that people use every single day. SQLite is an embedded library that implements a self contained, serverless, zero configuration, transactional SQL database engine. The code for SQLite can be used for commercial and private purposes. SQLite is the most used database in the world, with many high-profile projects and more applications than we can count.
  • 3
    IBM Db2 Reviews
    IBM Db2®, a family of hybrid data management tools, offers a complete suite AI-empowered capabilities to help you manage structured and unstructured data both on premises and in private and public clouds. Db2 is built upon an intelligent common SQL engine that allows for flexibility and scalability.
  • 4
    PostgreSQL Reviews

    PostgreSQL

    PostgreSQL Global Development Group

    PostgreSQL, a powerful open-source object-relational database system, has over 30 years of experience in active development. It has earned a strong reputation for reliability and feature robustness.
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