Speed of processing is an important aspect in choosing a data storage for time series data. The fast the better.
So how fast it is when NoSQL meet time series data? The following was what I found.
- Ubuntu 2.6.32-19-generic SMP 64bit
- Intel(R) Core(TM)2 Duo CPU T7500 @ 2.20GHz
- 2G memory
- 5400RPM hard disk
we have compared:
- Toyko Cabinet 1.4.44, B+ tree database
- Toyko Cabinet 1.4.44, table databse
- mongoDB snapshot-v20100520, multi-collections
- mongoDB snapshot-v20100520, one-collection with index
- redis 1.3.8
- mongo 1.0.1 with BSON_ext
- redis 1.0.4
I pushed it to github in case you want to roll you own results.
write 1M records
read last 30 days ohlc by symbol
read all ohlc by symbol
Results clearly shows Toyko Cabinet BDB was the winner.
This wasn't a full benchmark for NoSQL database, but more specific for time series data.