[lazy_kangaroo]

where did you get the 99% metric ? Most of the companies even with a single saas product have insane amount of data these days.

Not just application data, There is also a whole lot of analytical data collected at every step of the product usage cycle.

[traceroute66]

> where did you get the 99% metric ? Most of the companies even with a single saas product have insane amount of data these days.

I will just leave this link here ....

https://letsencrypt.org/2021/01/21/next-gen-database-servers...

[cutemonster]

And this one -- StackOverflow, one single live db:

https://stackexchange.com/performance

[KingOfCoders]

From managing databases over the last two decades (starting with Ingres/mSQL), hardware has growing much faster (RAM/CPU/NVMe) than the data needs. I remember the first time we put 2Tb RAM into a machine to handle most analytics in memory.

From my experience TimescaleDB is fast and takes a lot of data in. If you're multi tenant, it's usually easy to shard.

And we do dataware housing on BigQuery, no need to have your own machine and manage the database.

Of course there are people who need unlimited horizontal scaling.

[LoriP]

TimescaleDB also offers a good lot of supplementary functions to the PostgeSQL core product to help with time series data analysis... saves a lot of SQL acrobatics!

[jpgvm]

Generally you don't have your main application database also serve as your data warehouse for lots of reasons.

Generally you offload that to purpose built systems that favor those aforementioned tradeoffs or onto services that run them for you, i.e BigQuery, Snowflake, etc.

Your main application database is unlikely to need sharding unless you really do have a phenomenal amount of customers or you need regional sharding to meet legal requirements about data sovereignty for example.

[geon]

If you do sas, you are already the 1 %.

[mosselman]

You are right, the metric should probably be 99.999999999999999%. 99% is way to conservative.