What Are the Best Strategies for Scaling a MySQL/MariaDB Database?

Make sure you're not just blindly scaling hardware; there are also design issues to consider. Have a look at your table sizes and incoming request rates closely. If the app is struggling due to inefficiencies, try profiling it to identify problematic queries. Scaling should be more about resolving underlying issues rather than just adding more resources.

Switching to PostgreSQL is often suggested, but it's not a silver bullet; you’ll face similar scaling challenges with it too. Instead of jumping to a different DB, evaluate what your specific bottlenecks are. Figure out if the issues are related to queries, indexes, or overall design. Have you looked into optimizing your queries or using caching strategies?

For data splitting, consider implementing sharding. This involves computing a shard key for queries, making it easier to distribute data across different subsets. If your application is well-architectured, using an ORM can simplify transitioning. Just be aware that broad searches might get a bit trickier; you could set up a dedicated search database to handle that.

A great way to start is by adding a reader and splitting load at the application level. If you notice the read/write workload being heavily skewed, consider implementing multi-master setups like Galera, or exploring Vitess for better management of scaling issues. It all depends on your workload specifics—if it’s 90% reads, focusing on more readers can really help. Also, using ProxySQL could allow for effective traffic management and caching, which would offload some stress from your main database.

Before you panic about scaling, make sure to optimize your existing setup. Analyzing your queries, adding indexes, or even utilizing something like Redis for caching could alleviate some pressure. Keep in mind, moving to a system like PXC might help increase capacity without the need for a complete redesign.