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I'm at a company that is weighing a very similar decision (we are on RDS Postgres with a rapidly growing database that will require some horizontal partitioning). There really isn't an easy solution. We spoke to people who have done sharding in-house (Figma, Robinhood) as well as others who migrated to natively distributed systems like Cockroach (Doordash). If you decide to move off of RDS but stay on Postgres, you can run your own Postgres but now lose all the benefits of a managed service. You could move off of AWS (eg to Azure), but moving to a different cloud is a huge lift. That, btw, would also be required if you want to try something like Spanner (move to GCP). Moving off of Postgres to another database is also risky. The migration will obviously take some effort, but you're also probably talking about lots of code changes, schema changes, etc, as well as unknown operational risks that you'll discover on the new system. This applies if you're talking about things like Cockroach or even moving to MySQL. That said, rolling your own sharding is a MASSIVE undertaking. Limitless looks promising, since it takes care of a lot of the issues that Figma ended up spending time on (basically, you shouldn't need something like Figma's DBProxy, as shard routing, shard splitting, etc will be taken care of). It's still in preview though, and like the article mentioned, the costs may be high. Overall, no easy decisions on this one, unfortunately. |
It's a large challenge, but it's absolutely doable. A ton of companies did this 10-15 years ago, basically every successful social network, user generated content site, many e-commerce sites, massively multiplayer games, etc. Today's pre-baked solutions didn't exist then, so we all just rolled our own, typically on MySQL back then.
With DIY, the key thing is to sidestep any need for cross-shard joins. This is easier if you only use your relational DB for OLTP, and already have OLAP use-cases elsewhere.
Storing "association" type relation tables on 2 shards helps tremendously too: for example, if user A follows user B, you want to record this on both user A and user B's shards. This way you can do "list all IDs of everyone user A follows" as well as "list all IDs of users following user B" without crossing shard boundaries. Once you have the IDs, you have to do a multi-shard query to get the actual user rows, but that's a simple scatter-gather by ID and easy to parallelize.
Implementing shard splitting is hard, but again definitely doable. Or avoid it entirely by putting many smaller shards on each physical DB server -- then instead of splitting a big server, you can just move an entire shard to another server, which avoids any row-by-row operations.
Many other tricks like this. It's a lot of tribal knowledge scattered across database conference talks from a decade ago :)