What Happens inside MongoDB Time Series
Before We Start
We must talk about what Timeseries Data is.
Timeseries Data
A time series is a sequence of data points collected or recorded at successive points in time, typically at uniform intervals.
TimeseriesDB is Database that stores Timeseries Data.
How It differs from traditional DB?
It's always better to see, rather than explain.
 |  |
|---|---|
normal DB | Timeseries DB |
Features
As you can see, It Indexes Data by Time range.
Every Pros and cons comes from this.
- Made for storing large set of data
- Stores data chunks by time range
- Optimized for
INSERT&SELECT- Barely provides
DELETE&UPDATE
- Barely provides
Bucket Pattern
Before Timeseries, There was Schema Design Pattern, Bucket pattern.
It is primitive version of Timeseries collection.
I'll show you how to implement Bucket pattern.
Normally, you'd store data like left image.
indexing by id.
In Bucket Pattern, indexes data by time(start_date, end_date) and sensor_id.
This was efficient in 1:N relations, but were some issues.
If BSON size limit of 16 MB is exceeded, special handling needs to be performed, such as separating the loaded data and retrieving it again.
Starting from MongoDB 5.x, the support for Time series collection that internally implements the bucket pattern does the job for us.
etc
You might wanna see how data is actually stored.
Take a look at system.bucket.[COLLECTION_NAME].
{
"_id": "65d3eb80b6473e96f1b570c7",
"control": {
"version": 1,
"min": {
"_id": "65d418420498d3b000d19641",
"timestamp": "2024-02-20T00:00:00.000Z",
"data": {
"value": 0.04303943091823581
}
},
"max": {
"_id": "65d418f00498d3b000d1964b",
"timestamp": "2024-02-20T03:13:52.049Z",
"data": {
"value": 0.8827539992979445
}
}
},
"meta": {
"id": "6093b741070ad40011cabbae",
"key": "meta-data-you-set"
},
"data": {
"_id": {
"0": "65d418420498d3b000d19641",
"1": "65d418ec0498d3b000d19642",
"2": "65d418ed0498d3b000d19643",
"3": "65d418ee0498d3b000d19644",
"4": "65d418ee0498d3b000d19645",
"5": "65d418ee0498d3b000d19646",
"6": "65d418ee0498d3b000d19647",
"7": "65d418ef0498d3b000d19648",
"8": "65d418ef0498d3b000d19649",
"9": "65d418ef0498d3b000d1964a",
"10": "65d418f00498d3b000d1964b"
},
"timestamp": {
"0": "2024-02-20T03:10:58.414Z",
"1": "2024-02-20T03:13:48.823Z",
"2": "2024-02-20T03:13:49.553Z",
"3": "2024-02-20T03:13:50.025Z",
"4": "2024-02-20T03:13:50.371Z",
"5": "2024-02-20T03:13:50.671Z",
"6": "2024-02-20T03:13:50.952Z",
"7": "2024-02-20T03:13:51.272Z",
"8": "2024-02-20T03:13:51.490Z",
"9": "2024-02-20T03:13:51.738Z",
"10": "2024-02-20T03:13:52.049Z"
},
"data": {
"1": {
"value": 0.6954380762758321
},
"2": {
"value": 0.8276404308193761
},
"3": {
"value": 0.06242745352637269
},
"4": {
"value": 0.548645414603997
},
"5": {
"value": 0.8495674421359376
},
"6": {
"value": 0.04303943091823581
},
"7": {
"value": 0.6313514590828619
},
"8": {
"value": 0.8827539992979445
},
"9": {
"value": 0.1477508498242106
},
"10": {
"value": 0.818804826373378
}
}
}
}
