![]() ![]() ![]() Vertical sharding is similar to our “multiple databases” strategy in terms of setup and pros and cons, so we will not discuss it again. Have the same schema across all nodes, but distribute data depending on certain parameters (horizontal sharding).Distribute different tables on different nodes (vertical sharding).There are two strategies to shard your database: It will add considerable complexity to your application and needs to be done right to provide any real benefit. This is the most complex of all the methods for scaling databases discussed in this post. Database Sharding in Your Rails Application What can you do if your application still has a huge load on your primary database? The answer: database sharding. We'll add a log_default entry for the secondary database with a common configuration across all environments:Ĭlass MyAppSchema < GraphQL::Schema tracer Tracers :: DatabaseRoleTracer. Let's see how we can set this up.įirst, set up the database.yml to configure the second database. You should go for a separate database server if - and only if - there is a clear distinction between the parts of your app that will use different databases.įor example, a separate database is useful when you're audit logging in a high-frequency app (or have other very high-volume data that isn't necessarily accessed frequently). Alternatively, maybe there's one very database-heavy feature, but it is only used rarely or by a small section of users. For example, your app might do two different things that don’t have a big overlap. ![]() Sometimes, simply using a separate database server for a part of your app is a good solution. A Separate Database for Your Rails Application But usually, a good indicator of whether you need to optimize is if your database is always running at high CPU or memory usage. This will, of course, be different for different apps. Let's get going! Disclaimer: Scaling Isn't Always NeededĪs always, with any post about performance optimization and scaling, I would like to put up a standard disclaimer: make sure you have an issue before trying to solve it.įor example, on one of our apps in production, we tackled scaling and optimization only when we started processing more than 3 million background jobs a day. Splitting schema and data between multiple databases.This post will cover some alternative methods to fine-tune and scale a database under heavy load and improve the performance of your Rails app. You can't keep adding/removing CPU power or memory from the database server based on your load. This is also usually a one-way operation. You might have to copy all your data to the new server and then put the application down to change the database servers that it communicates with. This means adding more CPU power and memory to the database server. One way to tackle this is to grow a database with an app using vertical scaling. But eventually, the database needs to keep up with all the new connections from these processes. We keep scaling web servers and background workers to keep up with the heavy load. And as applications grow, databases grow too. Web applications usually rely heavily on databases, for the most part. ![]()
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