Understanding Tags and Fields in InfluxDB
Written on December 1, 2024
In InfluxDB, tags and fields are essential components used to organize and query time-series data. Here’s a detailed explanation of each:
Tags
Definition
Tags are key-value pairs used to categorize and filter time-series data. Tags are indexed, making them ideal for querying and grouping data efficiently.
Characteristics
- Stored as strings.
- Indexed for fast queries.
- Best suited for data with a finite number of unique values (e.g., categories, labels).
Example
If you’re storing temperature data from sensors in multiple locations:
- Tag Key:
location - Tag Value:
office,warehouse,store
Fields
Definition
Fields are key-value pairs that store the actual measurements or values of the data. Fields are not indexed, so they are optimized for storage and retrieval rather than filtering.
Characteristics
- Can store strings, integers, floats, or booleans.
- Not indexed (slower for filtering compared to tags).
- Used for storing metric or measurement values.
Example
In the same temperature dataset:
- Field Key:
temperature - Field Value:
23.5,25.0,22.8
Comparison Table
| Aspect | Tags | Fields |
|---|---|---|
| Purpose | Categorization and filtering | Storing metric values (measurements) |
| Indexing | Indexed (fast for queries) | Not indexed (optimized for storage) |
| Value Type | Strings | Strings, integers, floats, booleans |
| Example | location=office |
temperature=23.5 |
By understanding the difference between tags and fields, you can design your InfluxDB schema to balance performance and storage efficiency effectively.