Local Analysis of Garmin Activities and Fitness Data without Cloud

Arpan Ghosh — Thu, 16 Apr 2026 14:48:43 +0000

A high-performance, local-first analytics dashboard for your Garmin FIT files, built with Rust and DuckDB.

If you are a runner, cyclist, or data-driven athlete, you probably rely on cloud platforms like Garmin Connect or Strava to track your progress. While these platforms offer great social features, they also mean your personal health and telemetry data is locked up in a third-party ecosystem. What if you want rapid offline access, custom analytics, or simply total privacy and control over your own workouts in a modern, sleek, interactive desktop app dashboard that works on your PC, regardless if it’s Windows, MacOS or Linux?

Enter FIT Dashboard — an open-source, lightning-fast activity analytics dashboard designed specifically for Garmin Activity .fit files. Available as a standalone desktop application or a self-hosted Docker web app, FIT Dashboard is built for performance and data ownership. Take a look at the interface here.

Why FIT Dashboard?

The core philosophy behind FIT Dashboard is simple: your data should be yours, and exploring it should be blazing fast. You should be able to see overview stats, individual exercies, and compare one activity with another. Here is what sets it apart from traditional cloud-based trackers:

1. High-Performance Analytics with DuckDB

Handling hundreds of activities with millions of data points (heart rate, cadence, power, GPS coordinates) can bring traditional databases to a crawl. FIT Dashboard leverages DuckDB, an embedded analytical database, to perform rapid aggregations and automatic down-sampling for time-series queries. The result? Instantaneous chart loading and filtering, no matter how many marathons you’ve logged.

2. Deep Interactive Visualizations

The dashboard doesn’t just show you static numbers. It features interactive telemetry charts powered by ECharts, visualizing speed, heart rate, cadence, altitude, power, and temperature. You can zoom and pan seamlessly. Alongside the charts is a dynamic Activity Map built on MapLibre GL. Your route path changes color dynamically based on the metric you are analyzing (e.g., turning red when your heart rate spikes), and hover tool-tips provide exact telemetry details at every GPS coordinate.

3. Total Privacy & Flexible Deployment

Because it parses FIT files natively using Rust, your data never leaves your machine unless you want it to.

Desktop App: Built with Tauri v2, you can run it natively on Windows, macOS, or Linux.

Self-Hosted: Prefer a web-based approach? You can deploy it on your home server using the pre-built Docker image. It even includes session-based authentication and password protection out of the box.

4. Seamless Data Portability

Data lock-in goes both ways. FIT Dashboard makes it incredibly easy to bulk export your filtered activities. Need to move your data elsewhere? You can export single or batch workouts to CSV, JSON, GPX, or KML formats with a single click.

Under the Hood: A Modern Tech Stack

For the developers and tech enthusiasts, FIT Dashboard is a masterclass in modern, performant app architecture:

Backend (Rust): Powers the robust data processing. It uses the native fitparser crate for extraction without relying on external tools. Depending on how you run it, it utilizes either the Tauri framework for desktop or Axum for the REST API Docker deployment.
Database: DuckDB handles the heavy lifting of analytical queries and time-series downsampling.
Frontend (React 18 & TypeScript): Kept lightweight and snappy using Vite and Zustand for state management.
UI/UX: A beautiful glassmorphism design with instantaneous Dark/Light theme toggling, all built on clean CSS variables.

How to Get Started

Getting your data into FIT Dashboard is straightforward. First, you can request a bulk export of your data directly from Garmin’s data management portal (which will give you a ZIP file of all your historical .fit files).

From there:

Download the Desktop App: Head over to the Releases page on GitHub and grab the binary for your OS (Windows .msi/.exe, macOS .dmg, or Linux .AppImage/.deb).

Or Deploy via Docker: Run docker compose up -d using the provided configuration to spin it up on your local network.

Import: Drag and drop your Garmin .fit files into the import queue. The app will sequence the processing and automatically detect duplicates.

Final Thoughts

We are living in an era where we generate gigabytes of personal health and fitness telemetry. Relying solely on cloud providers to store and visualize this data leaves us vulnerable to platform changes, paywalls, or internet outages.

FIT Dashboard is a brilliant open-source solution that proves you don’t need to sacrifice beautiful UI or performance to own your data.

Ready to take control of your fitness data? Check out the project, download a release, and consider giving it a star on GitHub: Fit Dashboard Github.

How I Built a Free Tool to Visualize Garmin Health Data in Grafana Dashboards

Arpan Ghosh — Mon, 21 Apr 2025 08:54:12 +0000

Garmin devices collect an impressive amount of health and fitness data: heart rate, sleep, stress, respiration, SpO2, and more. But if you’re like me, you’ve probably wished for more flexibility in how that data is presented — and ideally, a way to combine it with other self-tracking sources.

So I built Garmin-Grafana: an open-source Python application that fetches Garmin data and feeds it into InfluxDB, so you can create rich, customizable health dashboards using Grafana. This script is available as a containerized docker application for easy deployment.

It’s free, open-source, and designed for people who love data — athletes, biohackers, or developers like me who want full control over their health visualizations.

What Garmin-Grafana Does

At its core, Garmin-Grafana automates the process of:

Authenticating your Garmin account
Fetching health, heart rate, sleep data, and activity data periodically
Storing the data in InfluxDB database
Visualizing the data using Grafana dashboards

You can track:

Heart Rate Data
Hourly steps Heatmap
Daily Step Count
Sleep Data and patterns (SpO2, Breathing rate, Sleep movements, HRV)
Sleep regularity heatmap (Visualize sleep routine)
Stress Data
Body Battery data
Calories
Sleep Score
Activity Minutes and HR zones
Activity Timeline (workouts)
GPS data from workouts (track, pace, altitude, HR)
And more…

You can easily pull your past historical data using this tool, no matter how far it goes back. So if you are a long term Garmin user, this tool will serve you well.

Data is yours. Host it privately. Visualize it however you want.

Why I Built It

I wanted a personal health dashboard that could:

Go beyond Garmin Connect’s limited graphs — the Grafana panels are infinitely customizable.
Be fully open, self-hosted, and free of cloud lock-in
Keep a local copy of my own health data for long term trend analysis

InfluxDB and Grafana are perfect for time-series data — but Garmin doesn’t provide a public API for personal health data access. So I wrote a workaround using the unofficial Garmin API that syncs the data on a schedule and populates it in the InfluxDB database.

How to Get Started

It’s surprisingly easy to set up if you’re familiar with Python and Docker. Otherwise, following the detailed guide will still get you there.

Please check out the GitHub project page for the installation instructions.

Example Dashboards

Here’s a quick look at what you can build. I have provided this sample dashboard JSON as a quick start.

Privacy First

Your health data stays local. No third-party services. No cloud sharing (You share it only with Garmin as they are the service provider). If you’re privacy-conscious or just want ownership over your data, this setup is for you.

Feedback or Collaboration?

I’d love to hear from you! Whether you’re using the tool, customizing it, or want to contribute — feel free to open an issue or drop me a message.

If you’re into self-tracking, open data, or wearable hacking, I hope this helps you dig deeper into your Garmin insights. Follow me for more open-source tools and personal data projects.

Let’s keep exploring what our devices can really tell us.

DEV Community: Arpan Ghosh

Local Analysis of Garmin Activities and Fitness Data without Cloud

Why FIT Dashboard?

1. High-Performance Analytics with DuckDB

2. Deep Interactive Visualizations

3. Total Privacy & Flexible Deployment

4. Seamless Data Portability

Under the Hood: A Modern Tech Stack

How to Get Started

Final Thoughts

How I Built a Free Tool to Visualize Garmin Health Data in Grafana Dashboards

What Garmin-Grafana Does

Why I Built It

How to Get Started

Example Dashboards

Privacy First

Feedback or Collaboration?