Certain time series databases tend to me be optimized towards making the most recent data readily available and quick to fetch. There are also certain filtering / compression algorithms that are run on these time series databases that only make sense in a time domain.

Also, some of these time series databases have very specific use cases and you have to also think about the client tools associated with the database. Many of these databases sit in power plants, factories, etc. and they stream data to tools that are built to visualize or analyze the last few minutes of data and then trigger alerts based on patterns. Also, these database are very "device" aware and integrates with other systems that represent their data in a timeseries fashion already (like a sensor). A lot of customers who needed this type of database care only about this index because their concern is record keeping and monitoring. Not necessarily number crunching (this is changing though).

There are drawbacks to storing your data this way. If your primary index is time, it can be hard to merge that with some based on a coordinate system. So doing certain types of analysis is really difficult unless you replicate your data into some other database with a different index.