Sensor data for industrial IoT - Architectural question

Hi all, we are currently working on a project using Grafana as visualizations dashboard. We are deeply involved with AWS so we are using this to gather data and to store them into an influxDB. The architecture is quite new so we are discussing some possibilities and best way to develop what we need. AWS will receive data from the sensor (IoT data) and after some processing it will store them into an influxDB. Grafana will then pull the data for visualization. All this has already been developed but we have noticed (we are quite new to timestream DB so please forgive me if I am asking silly questions) that because of the processing through AWS, the timestamp for the sample may not be exactly the same of when the sample was gathered. It will be with some seconds of delay, we are storing the real timestamp (epoch in us) of when the sample was gathered and they differ. Also, some sensors will work in offline mode and only occasionally have internet access, so it is vital to use the timestamp of when the sample was taken. I understand there is no way for Influx to force` a different timestamp, so our questions are:

  1. Is there any other DB which allows us to force the timestamp?
  2. Because we still have the real timestamp stored in the DB, would be just easier to show the sample in the graph using this field instead of the timestamp (time field) from the DB itself.

I would assume that being highly optimized DB, it could be that Grafana cannot even GROUP data with anything else then the timestamp from the DB…?

AWS is our preferable option, as we can also add extra processing to the data, but we are really opened to any alternative if we cannot solve the problem with the timestamp.

And also, thank you all in advance to anyone willing to help.