we were able to use a brin index for our time-series data and that saved
a lot of space. basically, we used a btree for recent data and, once the
data was "stable", reclustered the data to get high correlation on the
brin index, created a brin index and dropped the btree. it works well.
On 4/15/2019 1:42 AM, Ray Cheung wrote:
Hi ,
We are currently contemplating switching from MySQL to PostgreSQL, the main
attraction being the use of the TimescaleDB extension. Having done much of
the ground investigation there is one area of significant concern - the
storage requirement of PostgreSQL. Put simply, comparing like for like for a
set of tables, PostgreSQL consumes far more storage space than MySQL:
- MySQL (5.6): 156 MB
- PostgreSQL (11.2): 246 MB
- PostgreSQL + TimescaleDB (partitioned/chunked data): 324 MB
I've also submitted this in stackoverflow:
https://stackoverflow.com/questions/55655272/how-to-reduce-postgresql-databa
se-size.
I can rearrange the table/column-alignment to save 6 bytes per row of the
main table, with a saving of a few mega-bytes. Not enough to make any real
difference. Does anyone know:
- Why PostgreSQL is so storage inefficient in comparison?
- What existing methods can be used to reduce the storage consumption (I've
already tried realignment and vacuum full)?
- Are there any plans to address this storage consumption inefficiency (in
comparison to MySQL) problem?
Many thanks,
sps-ray
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