Re: Using Postgres to store high volume streams of sensor readings

On Fri, Nov 21, 2008 at 02:50:45PM +0200, Ciprian Dorin Craciun wrote:
>     Hello all!
>
>     I would like to ask some advice about the following problem
> (related to the Dehems project: http://www.dehems.eu/ ):
>     * there are some clients; (the clients are in fact house holds;)
>     * each device has a number of sensors (about 10), and not all the
> clients have the same sensor; also sensors might appear and disappear
> dynamicaly; (the sensors are appliances;)
>     * for each device and each sensor a reading is produced (at about
> 6 seconds); (the values could be power consumptions;)
>     * I would like to store the following data: (client, sensor,
> timestamp, value);
>     * the usual queries are:
>         * for a given client (and sensor), and time interval, I need
> the min, max, and avg of the values;
>         * for a given time interval (and sensor), I need min, max, and
> avg of the values;
>         * other statistics;
>
>     Currently I'm benchmarking the following storage solutions for this:
>     * Hypertable (http://www.hypertable.org/) -- which has good insert
> rate (about 250k inserts / s), but slow read rate (about 150k reads /
> s); (the aggregates are manually computed, as Hypertable does not
> support other queries except scanning (in fact min, and max are easy
> beeing the first / last key in the ordered set, but avg must be done
> by sequential scan);)
>     * BerkeleyDB -- quite Ok insert rate (about 50k inserts / s), but
> fabulos read rate (about 2M reads / s); (the same issue with
> aggregates;)
>     * Postgres -- which behaves quite poorly (see below)...
>     * MySQL -- next to be tested;

For this case I would use RRDTool: http://oss.oetiker.ch/rrdtool/

Regards,
  Gerhard