3 ms·
For us, it boiled down to multi-master writes, and global replication (multi-datacenters). Cassandra worked best for our use case. Moreover, as others have poin
by l8again 11y ago
For us, it boiled down to multi-master writes, and global replication (multi-datacenters). Cassandra worked best for our use case. Moreover, as others have pointed out, high availability with fault tolerance is another major reason. CAP theorem is real, and there are trade-offs to be made in several use cases.
- merb 11y agoStill with Cassandra you loose trnsactions and you can't start "small", as small as you could start with postgresql. A 10000 user service works well with a database running on 512mb ram, while cassandra needs at least 1gig (running lower could work there also, however mostly you will run into longer gc pauses than, it's really hard to trim the jvm down to less. I mean there are some ways to do it but it's way harder than just using something different). and mostly people start with as low as 10.000 people. Scaling means starting from 1 going to X. and postgresql is well enough for most stuff. You don't need multi-master replication for most stuff. people mostly don't need write scalability. and for stuff that needs some writes they could easily cache that. (see instagram)