Scattered vs Synchronised Data Sources
There are two ways that dates and times tend to be stored in databases.
They can be synchronised, meaning that every measurement is performed at the same effective time - for example, every point will be recorded every 10 seconds, and each point in that sample pass will have the same timestamp.
| Name | Time | Sample |
|---|---|---|
| Channel A | 4:00:00 | 12 |
| Channel A | 4:00:10 | 12.2 |
| Channel A | 4:00:20 | 12.4 |
| Channel B | 4:00:00 | 4 |
| Channel B | 4:00:10 | 5 |
| Channel B | 4:00:20 | 6 |
| Channel C | 4:00:00 | 3 |
| Channel C | 4:00:10 | 2.8 |
| Channel C | 4:00:20 | 2.6 |
Or they can be scattered, meaning that samples are taken at different times and time stamps are quite randomised.
| Name | Time | Sample | |
|---|---|---|---|
| Channel A | 3:59:12 | 12 | |
| Channel B | 4:00:00 | 4 | |
| Channel B | 4:00:30 | 6 | |
| Channel C | 4:00:10 | 3 | |
| Channel C | 4:00:15 | 2.7 | |
Database drivers support both kind of data source. However, synchronised data sources query significantly faster than scattered ones, because it is much more efficient to look up the previous sample time for one channel than it is to find the previous sample time for thousands.