---
title: Tags & Labels
slug: concepts/tags-and-labels
docTags: 11HRbizM9olUCcNKOmSMd,1v0vBxLIlIXilwWFGP6Rc
createdAt: 2025-07-17T11:51:36.529Z
---

## What are Tags & Labels?

In Factry Historian, **tags** and **labels** are two separate but complementary ways of attaching metadata to your [Measurements](docId\:XQWLEmDcNfff3-0H-GMmS) and [Calculations](docId\:OpIoDkGNNgYjeDX6zkg_D).

- **Tags** are written into the time-series database together with each data point. They are part of the underlying storage structure (e.g. in InfluxDB).
- **Labels** are managed within Factry Historian itself. They are used to group, filter, and organize data for data management, or forwarding.

## Why does it matter?

Both tags and labels help you make sense of your data at scale. They enable you to:

- Filter or group measurements by metadata (such as product, location, or asset type)
- Route specific subsets of data to external systems using [Forwarders](docId\:TD6EMj3F_0XsGJI7p4dAg)
- Keep your system maintainable as your setup grows

Using tags and labels consistently allows you to manage hundreds or thousands of signals without relying on naming conventions alone.

## How does it fit in the system?

### Tags (TSDB-level)

Tags are part of each data point in the time-series database. In InfluxDB, they are indexed key-value pairs used for fast querying and grouping. They are attached at **write time**, meaning they must be defined prior to the data being written.

**Example:**
A temperature measurement might be stored with the following tags:

- asset=Line1.Furnace
- unit=Celsius
- phase=heating

You can use these tags to filter data in dashboards or aggregate across a group.

### Labels (Historian-level)

Labels are maintained in Factry Historian and apply to measurements and calculations. They are used to:

- Categorize data sets for easy management
- Select subsets of data for forwarding to external systems using the [Forwarders](docId\:TD6EMj3F_0XsGJI7p4dAg) feature

Labels can be changed at any time without touching the underlying TSDB.

**Example:**
You might apply these labels to a set of measurements:

- Energy
- Team A
- Forward\_to\_Corporate

These labels can then be used to filter data while administering Factry Historian, or to selectively forward it.

## Example

Let’s say you have energy meters on five different lines.

Each measurement is written with the following **tags**:

- line=Line**X** (with X from 1 to 5)

Inside Factry Historian, you assign **labels** to all five energy measurements:

- Energy
- Forward\_to\_Corporate

You now have:

- Fast filtering by line using tags
- Centralized control over what gets forwarded to the corporate MQTT broker

## When you use it

You use **tags**:

- During data collection and ingestion
- For filtering and grouping in dashboards and queries
- To optimize time-series queries on indexed fields

You use **labels**:

- To manage configuration and routing within Factry Historian
- To group signals by purpose, not just origin
- When using the Forwarders feature to send specific sets of data to other systems

## Common misconceptions

- Tags and labels are not interchangeable. Tags live in the TSDB and are fixed once written. Labels are managed in the Historian and can be updated at any time.
- Tags must be defined before data arrives. Labels can be applied later.
- Labels do not affect how data is stored in the TSDB, only how it is used and organized within the application.

## Best practices

- Use tags for static metadata tied to the source of the data, such as asset or product.
- Use labels for categorization of data (e.g. energy, quality, process).
- Apply labels consistently across similar measurements to make administration and forwarding easier.

## More information

- [Creating and deleting labels](docId\:MC0qkxEw3EaffwRL94DxA) 
- Configuring [forwarders](docId\:TD6EMj3F_0XsGJI7p4dAg) using labels