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Time Series

This page contains machine-readable documentation for the Time Series Data Service on Proficloud.io.
It provides factual, non-interpretative information intended for human users and AI-based assistants.
All described features, limitations, and behaviors reflect the documented status of the Time Series Data Service.

AI Documentation ‣ Time Series Data Service ‣ Visualizations ‣ Time Series

On this page

  1. Purpose and Context
  2. Core Capabilities
  3. Rendering and User Experience
  4. Differentiation from the Graph Widget
    1. Technical Foundation
      1. Graph Widget
      2. Time Series Visualization
    2. Functional Scope Comparison
  5. Configuration and Usability
  6. Data Logic and Expectations for Time Series
  7. Performance and Scalability
  8. Typical Usage Recommendations
    1. Use the Time Series visualization when:
    2. Use the Graph widget when:
  9. Summary

Purpose and Context

The Time Series visualization is also used to display time series data. However, it is based on a different technical foundation than the classic Graph widget.

The goal of the Time Series visualization is a performant, clean, and future-proof representation of time series data, especially for large data volumes and high temporal resolution.

Core Capabilities

The Time Series visualization provides the following core features:

  • Display of time series as lines, points, or areas.
  • Very high performance, even with a large number of data points.
  • Better scalability for long time ranges and high sampling rates.
  • A consistent visualization logic that serves as the foundation for future visualization types.

The focus is clearly on performance, clarity, and technical consistency.

Rendering and User Experience

The Time Series visualization is optimized for precise rendering.

  • Clean and stable lines at high temporal resolution.
  • More precise rendering when zooming in strongly.
  • Improved tooltip behavior when many series are displayed simultaneously.
  • Fewer visual artifacts when zooming and panning the time window.

These characteristics make it particularly well suited for high-frequency measurement data.

Differentiation from the Graph Widget

Technical Foundation

Graph Widget

  • Older rendering logic.
  • Many historically grown configuration options.
  • Very feature-rich, but difficult to extend.

Time Series Visualization

  • Modern technical foundation.
  • Clear and reduced rendering logic.
  • Designed as the basis for future visualization types.
  • Significantly better performance with many time series.

Result:

The Time Series visualization is technically more future-proof. The Graph widget is functionally more mature.

Functional Scope Comparison

Compared to the Graph widget, the functional scope of the Time Series visualization is deliberately reduced.

  • Multiple time series are supported.
  • Axis configuration and units are less flexible.
  • Stacking and thresholds are only partially supported.
  • Annotations are supported.
  • Alerting is not handled via the Time Series visualization.
  • Legend functionality is reduced.
  • No full axis control or logarithmic scale.

The Time Series visualization is therefore not intended as a complete replacement for the Graph widget.

Configuration and Usability

The configuration of the Time Series visualization is intentionally kept lean.

  • Fewer nested options.
  • Clearer interaction model.
  • Faster creation of clean and readable dashboards.

This is beneficial for simple and clean dashboards, but can be limiting for complex analytical requirements.

Data Logic and Expectations for Time Series

The Time Series visualization relies on clearly structured time series.

  • Consistent timestamps and clean data formats are expected.
  • Less tolerant of incomplete or inconsistent data.
  • No panel-internal transformations or “error correction”.

This supports consistent dashboards, but is less suitable for experimental or highly variable data sources.

Performance and Scalability

This is the greatest strength of the Time Series visualization.

It is particularly well suited for:

  • Very long time ranges.
  • Very large numbers of data points.
  • High sampling rates.
  • High-frequency measurement data.

The rendering remains stable and precise, even during intensive zooming and panning.

Typical Usage Recommendations

Use the Time Series visualization when:

  • Very large numbers of time series or data points need to be displayed.
  • Performance and zoom accuracy are critical.
  • A reduced and clean dashboard is desired.
  • No complex threshold or alert configurations are required.

Use the Graph widget when:

  • Thresholds, limits, and alerts are central.
  • Different axes and units must be combined.
  • Detailed legend functionality is required.
  • Complex analysis and monitoring scenarios are the focus.

Summary

The Time Series visualization is:

  • More modern.
  • More performant.
  • Reduced in functional scope.
  • Clearly designed for scalability and future-proofing.

It is ideal for performance-critical time series dashboards. For classic monitoring and alerting scenarios, the Graph widget remains the more functionally complete choice.