Scaling Databases For Global Serverless Applications

Polyscale is a no-code database edge cache that distributes data and query compute closer to the user. It functions by caching database data at the edge or closer to the user and also offers the compute itself. This means if you have a unique SQL query, it will execute against Polyscale's Points of Presence (POPs) and return the data from Polyscale if it is in the cache.

To connect a database to Polyscale, update your database credentials such as the host name and database username to route through Polyscale. For MySQL and MariaDB, include your cache ID in the database username. For Postgres, pass the cache ID as the application name parameter.

As of the information provided, Polyscale currently supports MySQL, MariaDB, and Postgres. Support for Microsoft SQL Server is planned and forthcoming, while MongoDB support is also under consideration for future updates.

Polyscale can potentially replace Redis or other application-level caching solutions, especially in scenarios where you want to reduce complexity and avoid managing caching logic at the application level. Polyscale manages caching at the data tier, which can simplify operations.

Polyscale caches DQL (Data Query Language) queries, which include 'select' and 'show' queries. It automatically handles and optimizes caching for these queries based on frequency and other factors using AI and machine learning technologies.

Polyscale ensures data security by not storing database usernames or passwords, and all data remains SSL encrypted during transit. Users can also deploy Polyscale within their own networks for enhanced compliance and control, ensuring that cached data never leaves their environment.

Yes, Polyscale allows manual configuration of caching rules where you can specify custom rules for individual SQL queries or set default behaviors for caching. This provides flexibility in managing how data is cached based on specific application needs.

Polyscale offers significant benefits for global applications by reducing latency and improving data access speed across different regions. It caches data closer to users and distributes query compute globally, which helps in maintaining high performance even when scaling applications internationally.