Recent submissions

Comment · 7 years ago
CPU usage varies based the selected compression algorithm and level used. Snappy and LZMA area available now. Compression is native code. There are some newer interesting algorithms (zstd/lz4) that we are looking into adding.
Comment · 7 years ago
One of the pghoard developers here. We developed pghoard for our use case (https://aiven.io):

* Optimizing for roll forward upgrades in a fully automated cloud environment * Streaming: encryption and compression on the fly for the backup streams without creating temp files on disk * Solid object storage support (AWS/GCP/Azure) * Survive over various glitches like faulty networks, processes getting restarted, etc.

Restore speed is very important for us and pghoard is pretty nice in that respect, e.g. 2.5 terabytes restored from an S3 bucket to an AWS i3.8xlarge in half an hour (1.5 gigabytes per second avg). This means hitting all of cpu/disk/network very hard, but at restore time there's not typically much else to do with them.

Comment · 9 years ago
The next part in the series will include read-write benchmarking. Taking suggestions for other benchmark scenarios!
Comment · 9 years ago
We host a number of our customers' database systems on us-east-1.

What worked well for us (https://aiven.io):

- Architecturally relying only to a few cloud provider services (only need VMs, disk, object storage)

- Upfront investment on being able to move services from one region to another without downtime

- Pre-existing tooling for easily (manually) reconfiguring backup destinations on the fly

- Not running everything on just AWS

What did not work so well:

- Backups should automatically reroute to a secondary backup site on N consecutive failures

- Alert spam, need more aggregation

- New failure mode: extremely slow EBS access, some affected VMs were kinda working, but very slowly: need to create a separate alert trigger for this

Comment · 9 years ago
Comment · 10 years ago
We provide UpCloud as one of the cloud options for our SaaS database/metrics/messaging offering at Aiven.io and have been extremely happy with their disk i/o performance.

Here's just a quick "hdparm -t" test I just ran on two random low-end nodes:

upcloud-de-fra: 1028 MB in 3.00 seconds = 342.12 MB/sec

aws-us-west-1: 58 MB in 3.02 seconds = 19.17 MB/sec

I would of course recommend everyone to benchmark their actual workload on each cloud option before making the decision.

Comment · 10 years ago
From the Release Notes:

Major enhancements in PostgreSQL 9.6 include:

Parallel sequential scans, joins and aggregates

Elimination of repetitive scanning of old data by autovacuum

Synchronous replication now allows multiple standby servers for increased reliability

Full-text search for phrases

Support for remote joins, sorts, and updates in postgres_fdw

Substantial performance improvements, especially in the area of improving scalability on many-CPU servers

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