Hi,
I have run a test with pgbench against two cloud vendors (settings, parameters almost the same).
Both Postgres (or whatever they do internally when they call it
as Postgres offering, NOT Aurora or so :-) )
I have got a strange result that cloud vendor 1 is performing almost everywhere better in matter of
read and write but except in the init phase of pgbench it took almost double the time.
pgbench -i -IdtGvp -s 3000 "${PG_DATABASE}"
pgbench -c 50 -j 10 -P 60 -r -T 3600 "${PG_DATABASE}"
| Metric | cloud vendor 1 (small) | cloud vendor 1 (large) | cloud vendor 2 (small) | cloud vendor 2 (large) | |----------------------------------|------------------------|------------------------|-------------------|-------------------| | **Initialization Time** | 60m52.932s | 3h0m8.97s | 32m7.154s | 5h14m16s | | **Benchmark Duration** | 3600s (1 hour) | 3600s (1 hour) | 3600s (1 hour) | 3600s (1 hour) | | **Transactions per Second** | 399.460720 | 9833.737455 | 326.551036 | 3314.363264 | | **Latency Average (ms)** | 125.124 | 6.507 | 153.106 | 19.309 | | **Latency StdDev (ms)** | 154.483 | 44.403 | 59.522 | 4.015 | | **Initial Connection Time (ms)** | 557.696 | 174.318 | 1688.474 | 651.087 | | **Transactions Processed** | 1,438,437 | 35,400,215 | 1,175,081 | 11,929,631 | | Statement (ms) | cloud vendor 1 (small) | cloud vendor 1 (large) | cloud vendor 2 (small) | cloud vendor 2 (large) | |-----------------------------|------------------------|------------------------|-------------------|-------------------| | BEGIN | 8.599 | 0.545 | 9.008 | 1.398 | | UPDATE pgbench_accounts | 38.648 | 2.031 | 27.124 | 4.722 | | SELECT pgbench_accounts | 12.332 | 0.676 | 17.922 | 1.798 | | UPDATE pgbench_tellers | 17.275 | 0.853 | 20.843 | 1.831 | | UPDATE pgbench_branches | 18.478 | 0.862 | 21.941 | 1.743 | | INSERT INTO pgbench_history | 16.613 | 0.827 | 18.710 | 1.501 | | END | 13.177 | 0.708 | 37.553 | 6.317 |
Of course no one knows the magig underneath what some cloud vendors are doing underneath but does anyone have some
ideas what the reason could be or how I could do better testing
to find this out?
Cheers
Dirk
