Depending on what you are doing you can even try to write it yourself. It would be a good exercise.

Here is a toy hand crafted time series storage design:

Say you are storing tuples of {<timestamp>,<datablob>}. Then querying it by timestamp.

Writer can store it in two files,open in append only mode only. One is the data file one is the index file. Data might look like:

<datablob1><datablob2>...

And an index file, it stores timestamps and offsets into the data files where the blobs are:

<timestamp1><offset1><timestamp2><offset2>...

If you need rolling fall-off. Then create new pairs of files every day (hour, week, month). And delete old ones as you go.

Then if you can ensure that your have time synchronization set up and timestamp are in increasing order (this might be hard). You can do binary searching. If you use rolling fall-offs. Then you can discard whole files periods based on the query range when you search.

All this would go into a directory. Reader and writer could be different processes. Your timestamp and offset sizes should be fixed length. Writer first appends to the data file and then writes the index. Reader knows how to find the last valid record by looking at the size of the file.