Here's a Medium post on Time Series Databases: https://medium.com/datadriveninvestor/what-are-time-series-d... But basically, they are databases where the time dimension is a critical aspect of the data. They handle never-ending streams of incoming time-stamped data. Think of streaming stock prices, or streaming temperature data from a sensor. You want to be able to query your data specifically in a time dimension -- let's see the temperature fluctuations over the past 24 hours, including the mean. Stuff like that.

A 'normal one' is typically used for things like transactional data which adds, deletes, and updates data among linked tables. While these transactions happen in time, the time component isn't necessarily a critical dimension of the data.