We are working on a SSD-backed key-value solution with the following properties:
We tried KyotoCabinet, LevelDB, and RethinkDB on commodity SSDs, with different Linux IO schedulers, ext3/xfs file systems; made a number of tests using Rebench; and found that in all cases:
The picture below illustrates such behavior for KyotoCabinet (horizontal axis is time, three periods are clearly visible - read-only, mixed, update only).
The question is: is it possible to achieve low latency for described SLAs using SSDs and what key-value stores are recommended?
Highly variant write latency is a common attribute of SSDs (especially consumer models). There is a pretty good explanation of why in this AnandTech review .
Summary is that the SSD write performance worsens overtime as the wear leveling overhead increases. As the number of free pages on the drive decreases the NAND controller must start defragmenting pages, which contributes to latency. The NAND also must build an LBA to block map to track the random distribution of data across various NAND blocks. As this map grows, operations on the map (inserts, deletions) will get slower.
You aren't going to be able to solve a low level HW issue with a SW approach, you are going to need to either move up to an enterprise level SSD or relax your latency requirements.
Aerospike is a newer key/value (row) store that can run completely off of SSDs with < 1ms latency for read/write and very high TPS (reaching into millions).
SSDs have great random read access but the key to reducing variance on writes is using sequential IO (this is similar to regular hard disks). It also greatly reduces wear leveling and fade that can occur with lots of writes on SSDs.
If you're building your own key-value system, use a log-structured approach (like Aerospike) so that writes are in bulk and appended/written in large chunks. An in-memory index can maintain the correct data locations for the values while a background process cleans stale/deleted data from disk and defrags files.
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