Database Reference
In-Depth Information
series databases (the subject of this topic). Remember that it's not just a matter of asking
yourself what data to save, but instead looking at
when saving data as a time series database
is advantageous
. At very large scales, time-based queries can be implemented as large, con-
tiguous scans that are very efficient if the data is stored appropriately in a time series data-
base. And if the amount of data is very large, a non-relational TSDB in a NoSQL system is
typically needed to provide sufficient scalability.
When considering whether to use these non-relational time series databases, remember the
following considerations:
Use a non-relational TSDB when you:
▪ Have huge amount of data
▪ Mostly want to query based on time
The choice to use non-relational time series databases opens the door to discovery of patterns
in time series data, long-term trends, and correlations between data representing different
types of events. Before we move to
Chapter 3
, where we describe some key architectural
concepts for building and accessing TSDBs, let's first look at some examples of
who uses
time series data and why
?
Stock Trading and Time Series Data
Time series data has long been important in the financial sector. The exact timing of events is
a critical factor in the transactions made by banks and stock exchanges. We don't have to
look to the future to see very large data volumes in stock and commodity trading and the
need for new solutions. Right now the extreme volume and rapid flow of data relating to bid
and ask prices for stocks and commodities defines a new world for time series databases. Use
cases from this sector make prime examples of the benefits of using non-relational time
series databases.
What levels of data flow are we talking about? The Chicago Mercantile Exchange in the US
has around 100 million live contracts and handles roughly 14 million contracts per day. This
level of business results in an estimated 1.5 to 2 million messages per second. This level of
volume and velocity potentially produces that many time series points as well. And there is
