SQL databases have supported the LIKE operator for a very long time and it will allow you to compare a string to a pattern and has wildcard characters to match any single character or zero or more characters. Informix also supports the MATCHES operator that give you some more wildcard matching options. Similar to the LIKE predicate, MATCHES has support for wildcard characters to match any single character or zero or more characters. It also has the ability to match single character from a set or range of characters or match a single character that is not in a set or range of characters. These are both examples of simple regular expressions.
With the advent of micro services architecture and DevOps model, enterprise architects expect database servers to operate in real-time environment, push data and events to clients rather than clients polling for data, scale linearly, enable zero downtime deployments, and easy integration with other middleware services like enterprise message bus.
Databases are historically a great place to store data and retrieve data. However, they are not always the easiest to process events and receive alerts from, especially in real time or near real time. You can use a specialized software for this, but what if you wanted the best of both worlds? An enterprise level database for storage and security, but with the ability to process events and alerts as they happen.
This is the first part of a multi-part series on Informix TimeSeries, going into greater detail on how to setup, configure, and use the Informix TimeSeries solution.
What is Time Series Data?
A time series is a set of time stamped data. There are many different types of time series data, for example, stock prices, smart meters, network performance metrics and any type of sensor data. It could contain raw data readings or aggregation of data over periods of time. Informix TimeSeries provides a method of storing and analyzing data that goes beyond the capabilities of traditional relational databases. Informix TimeSeries provides storage savings and better query speeds when compared to a relational database.