Time Series Database - Overview

Overview

The TSDS allows users to create, enumerate, update and destroy various time series and organize them in some fashion. These series may be organized hierarchically and optionally have companion metadata available with them. The server often supports a number of basic calculations that work on a series as a whole, such as multiplying, adding, or otherwise combining various time series into a new time series. They can also filter on arbitrary patterns defined by the day of the week, low value filters, high value filters, or even have the values of one series filter another. Some TSDSs also build in a wealth of statistical functions.

For example, consider the following hypothetical "time series" or "profile" expression:

SELECT nymex/gold_price * nymex/gold_volume

To analyze this, the TSDS would join the two series nymex/gold_price and nymex/gold_volume based on the overlapping areas of time for each, multiply the values where they intersect, and then output a single composite time series.

Obviously, more complex expressions are allowed. TSDSs often allow users to manage a repository of filters or masks that specify in some way a pattern based on the day of a week and a set of holidays. In this way, one can readily assemble time series data. Assuming such a filter exists, one might hypothetically write

SELECT onpeak( cellphoneusage )

which would extract out the time series of cellphoneusage that only intersects that of 'onpeak'. Some systems might generalize the filter to be a time series itself.

This syntactical simplicity drives the appeal of the TSDS. For example, a simple utility bill might be implemented using a query such as:

SELECT MAX( onpeak( powerusagekw ) ) * demand_charge; SELECT SUM( onpeak( powerusagekwh ) ) * energy_charge;

TSDS also generally have conversions to and from specific time zones implemented at the server level.