Efficient way to store and retrieve big amount of data

I need to store a big amount of data (about 2.5 billion of new data rows per month), but also I need a very fast way to retrieve the latest value per group on specific time point. The data looking very simple: | ParameterId | Value | DateTime | |--------------|-------|---------------------| | 1 | 12.5 | 2023-04-21 14:35:03 | | 2 | 56.81 | 2024-03-01 16:21:17 | | 1 | 12.5 | 2024-05-22 14:35:03 | | 1 | 71.4 | 2024-05-31 18:27:03 | For example, we need the latest values by each parameter on 2024-04-31 17:40. The result will be as follows: | ParameterId | Value | DateTime | |--------------|-------|---------------------| | 1 | 12.5 | 2023-04-21 14:35:03 | | 2 | 56.81 | 2024-03-01 16:21:17 | This looks like it can be solved by a simple database storage, but I've some restrictions: 1. The disk storage is limited. That's why indexes cannot be used as it's almost an x2 of the data space 2. The max query time for any request is 5 seconds. 3. We have only 1 server I've already tried to use TimescaleDB (table partitioning), but because I've only right datetime condition (<= dt) it's very inefficient to search for the value in old chunks from the first one. Technically it's possible, because we have an old software developed by third-party company 10 years ago and it still working, but nobody knows how...