Scaling
CockroachDB nodes: 9, or even more, 7-19.
Emphasis on: Performance of insertions
Q: Use one huge DB table, or split data to more than one DB tables?
(or use partitioned table)
Table:
Hundreds of millions of rows in a table.
ID field, and Small JSON data in one column of one row.
Some test are being executed.
Other things to take in account?
Should reading be ok in both cases: using one huge table or X tables.
Hey @roachman,
Can we know a little bit more about your workload? Perhaps you could share a sample DDL?
What are your reads doing? Do you have a UUID or INT as a PK?
We would definitely need to know more about your overall workload before we could make some recommendations.
Thanks,
Ron
I am trying to test /reach best possible throughput. Inserts as fast as possible. Maximum possible rate.
bigint is in use as ID. It is PK.
I have seen difference in throughput with my setup. One third faster (or even more) with a couple/some tables in comparison to one table. Totally independent tables.
14-17 key value pairs in one json data entry. Quite small.
Emphasis is on scaling.
Do insertions scale/improve better with more than or equal to two tables in comparison to one huge table.
Multi row batch inserts are used (golang).
Language: golang, or java (either one).