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Turn fitness exports into repeatable, queryable tables with DuckDB and dbt—without needing a hosted warehouse. DuckDB can run embedded in memory or in a local database file; dbt provides the layer for organizing transformations into reusable models. “Serverless” here means you can avoid managing a database server, not that the local setup runs in the cloud.
What the setup does—and what it does not
Fitness history is often split across apps and devices. An export gives you files you can keep and analyze; DuckDB reads or stores the data, and dbt turns it into documented transformations you can rerun when you add another export.
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This workflow is based on files rather than a live connection to a fitness service. The documented Apple Health and Garmin paths below read exports; they do not establish automatic account syncing. You do not need to buy a wearable or create a hosted warehouse account to follow the local path.
Choose where DuckDB runs
| Choice | Where data is processed | When it fits |
|---|---|---|
| Embedded DuckDB | In memory or in a local database file on your machine | Start here for an individual, local-first workflow. |
| MotherDuck connection | Hosted connection documented as an option for dbt and DuckDB | Consider it if you specifically want hosted access; it is optional, not a requirement. |
The dbt setup documentation describes both local and MotherDuck connection options. DuckDB also documents reading from files, cloud storage, and databases, including CSV, JSON, Parquet, S3-compatible storage, Azure Blob Storage, Cloudflare R2, MySQL, PostgreSQL, and SQLite. These capabilities give you room to expand later; none is required for a local export-based start.
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Check the dbt route before building
Use the interface and product generation that match the setup you intend to run. The dbt v2 supported-platform page lists DuckDB as generally available for the CLI only, and notes that adapter lifecycle differs between local development and the dbt platform. Do not assume all dbt interfaces behave interchangeably.
The current dbt DuckDB setup page also flags two practical limits: the bundled driver does not support loading DuckDB extensions, and static analysis can have issues when models reference local CSV, Parquet, or JSON files through DuckDB file-reading functions. If your workflow needs an extension or direct file reads, follow the setup page’s system-installed-driver guidance and check the behavior for your version.
Rank #2
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Build a small local project from one export
Start with one export and a local DuckDB target. The exact dbt project commands depend on your installed dbt generation and environment; use the current DuckDB setup instructions for the CLI-only route rather than copying commands for a different interface.
- Prepare an export. Obtain an export from the service you already use and keep the original files unchanged. For Apple Health, the community
healthkit_exportextension readsexport.ziporexport.xml. For Garmin activity files, the communityfitextension reads.fitfiles. - Configure DuckDB locally. Choose an in-memory database for a temporary session or a local database file for a persistent working database. Keep the database and input files in locations you can back up.
- Make the raw data accessible. Follow the DuckDB/dbt setup appropriate to your version. If using a community extension, confirm that it is compatible and available through your chosen driver; the bundled dbt driver does not load DuckDB extensions.
- Create staging models. Make a model for each raw table or export input, with clear names and only straightforward cleanup at first. Preserve source fields while you establish what they mean.
- Build a canonical activity model. Map source records into a consistent shape, such as activity date, duration, distance, and source. Treat this as a design choice, not a guarantee that platforms use identical definitions or units.
- Add an aggregate only after checking the base model. A weekly activity-volume model or a summary by activity type can be useful, but confirm the underlying dates, units, and event definitions before combining platforms.
Apple Health and Garmin are file-ingestion options
The DuckDB Community Extensions listing describes healthkit_export as producing typed tables for records, workouts, activity rings, workout routes, and GPX points from an Apple Health export. It is a community extension maintained by Mjboothaus, not a DuckDB core feature.
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The community fit extension exposes records, activities, sessions, laps, and device information from Garmin .fit files. These extensions broaden the file inputs you can work with; they do not provide evidence of a live connection to Apple Health or Garmin accounts. Check their compatibility and installation instructions before using them.
Validate meaning, not just whether a query runs
A successful build proves that the transformation executed, not that two vendors’ measurements mean the same thing. Before trusting an aggregate, inspect sample records and check the source field definitions, units, time zones, and date boundaries.
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- Compare input and staging row counts to catch missing or duplicated records.
- Inspect the earliest and latest dates in each source to ensure the expected export range arrived.
- Check distance and duration values against several original records, including any unit conversions.
- Verify how workouts, activities, laps, and other event types are represented before combining them.
- Run the same models after adding an export and confirm that previously loaded history remains intact.
Direct references to local flat files can also be affected by dbt’s static-analysis limitations. If analysis reports a problem even though a DuckDB file-reading function is valid in your environment, consult the version-specific setup guidance and test the actual model behavior rather than treating static analysis as proof that the data is correct.
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Once the local model works, you can decide whether to keep reading files in place, move them to cloud storage, or use a hosted DuckDB connection. DuckDB documents sources including S3-compatible storage, Azure Blob Storage, and Cloudflare R2, as well as relational databases. The dbt-duckdb README describes MotherDuck connection strings and fsspec-backed storage paths.
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These are optional ways to access data, not prerequisites for a personal fitness warehouse. External files can simplify access to a growing collection, while hosted access can suit a workflow that needs it; both add configuration and a different trust boundary from a database file on your computer.
Keep the results portable
You can retain the DuckDB database file as your working analytical store, or export derived data when you want to use it elsewhere. DuckDB documents exporting a database to CSV or Parquet and importing that export into a fresh database. Its export/import documentation notes that the exported schema uses plain CREATE statements, so import into a fresh database rather than one that already contains the exported schema.
The dbt-duckdb documentation also describes external materialization for file outputs. Choose CSV when broad compatibility matters or Parquet when you want a columnar file format; use the format supported by the destination workflow you have in mind. Check the export syntax against the DuckDB version you are running.
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Quick Recap
Sources and version notes
- dbt Developer Hub: DuckDB setup and supported data platforms, accessed October 7, 2026.
- DuckDB: EXPORT and IMPORT DATABASE Statements, accessed October 7, 2026.
- dbt-duckdb README, rolling documentation accessed October 7, 2026; and Petrica Leuca, “Fully Local Data Transformation with dbt and DuckDB,” published April 4, 2025.
- DuckDB Community Extensions: healthkit_export and fit, listings accessed October 7, 2026.
- DuckDB: Data Sources, accessed October 7, 2026.
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