The reason why TimescaleDB is so fast relies really a simple concept; keep indexes small enough to keep in memory. If you have a small enough index, you only need to do 2 reads from disk; one for the index to locate the data, and then one for the actual data.
Fetching data becomes much, much slower once your index is too large to fit in main memory. TimescaleDB segments the indexes into chunks (the “hypertables”) and makes sure these chunks are all “small enough”.
This alleviated further by having the data sequential by time; inserting new data does not need to alter older index chunks, which is what makes inserts fast.
I can imagine that if that’s not the case and your inserts are altering “older” chunks so data needs to move between lots of chunks could make the database prohibitively slow.
Fetching data becomes much, much slower once your index is too large to fit in main memory. TimescaleDB segments the indexes into chunks (the “hypertables”) and makes sure these chunks are all “small enough”.
This alleviated further by having the data sequential by time; inserting new data does not need to alter older index chunks, which is what makes inserts fast.
I can imagine that if that’s not the case and your inserts are altering “older” chunks so data needs to move between lots of chunks could make the database prohibitively slow.