Strava connector

Set up the Strava connector in Kaivo: authentication, configuration, the 2 BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated 16 days ago

Kaivo is a fully managed data platform that syncs your Strava data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from Strava instead of moving it.

What is the Strava connector

Sync your Strava activity data into BigQuery with Kaivo to analyse training volume, performance, and trends across rides, runs, and swims.

Category	Other
Authentication	API key
Setup	Self-service

Getting started with the Strava connector

Sign up for Kaivo and create a workspace.
Connect your Strava account.
Choose which tables to sync.
Wait for the initial sync to finish.
Query your data in BigQuery or your favourite AI or BI tool.

Authenticating Strava

Authenticate with your Strava credentials. You provide:

Field	Description
Client Secret	The Client Secret of your Strava API application.
Refresh Token	The Refresh Token with activity:read_all permissions.

Prerequisites

Strava only supports OAuth, so you need your own Strava API application:

In the Strava developer portal, create an API application and note your Client ID and Client Secret.
Authorize the app to obtain a Refresh Token with read_all and activity:read_all scopes.
Find your Athlete ID in your Strava profile URL.

Then enter those values below.

Need help, or want an easier way to connect? Reach our team via the chat in the bottom-right corner.

Configuring the Strava connector

When you set up the connector, you provide:

Field	Description
Client ID	The Client ID of your Strava API application.
Athlete ID	Your Strava athlete ID.
Start Date	Any data before this date will not be fetched.

Tables and columns synced from Strava

Kaivo syncs 2 tables from Strava into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

activities (57 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`type`	`STRING`	Type of activity (e.g., ride, run)
`achievement_count`	`INT64`	Total number of achievements in the activity
`athlete__id`	`INT64`	ID of the athlete who completed the activity
`athlete__resource_state`	`INT64`	Resource state of the athlete
`athlete_count`	`INT64`	Total number of athletes linked in the activity
`average_speed`	`FLOAT64`	Average speed of the activity
`average_temp`	`FLOAT64`	Average temperature during the activity
`average_watts`	`FLOAT64`	Average power output in watts
`comment_count`	`INT64`	Total number of comments on the activity
`commute`	`BOOL`	Indicates whether the activity is a commute or not
`device_watts`	`BOOL`	Indicates if the power data is from a device
`display_hide_heartrate_option`	`BOOL`	Indicates if the heart rate option is hidden in the display
`distance`	`FLOAT64`	Total distance covered in the activity
`elapsed_time`	`INT64`	Total time elapsed during the activity
`elev_high`	`FLOAT64`	Elevation at the highest point of the activity
`elev_low`	`FLOAT64`	Elevation at the lowest point of the activity
`external_id`	`STRING`	External identifier of the activity
`flagged`	`BOOL`	Indicates if the activity is flagged by the athlete
`from_accepted_tag`	`BOOL`	Indicates if the activity is from an accepted tag
`gear_id`	`STRING`	ID of the gear used in the activity
`has_heartrate`	`BOOL`	Indicates if heart rate data is available for the activity
`has_kudoed`	`BOOL`	Indicates if the athlete has given kudos for the activity
`heartrate_opt_out`	`BOOL`	Indicates if the athlete has opted out of displaying heart rate
`id`	`INT64`	ID of the activity
`kilojoules`	`FLOAT64`	Total energy expenditure in kilojoules
`kudos_count`	`INT64`	Total number of kudos received for the activity
`location_city`	`STRING`	City where the activity took place
`location_country`	`STRING`	Country where the activity took place
`location_state`	`STRING`	State where the activity took place
`manual`	`BOOL`	Indicates if the activity was manually entered
`map__id`	`STRING`	ID of the map associated with the activity
`map__resource_state`	`INT64`	Resource state of the map
`map__summary_polyline`	`STRING`	Polyline of the route summary
`max_speed`	`FLOAT64`	Maximum speed achieved during the activity
`max_watts`	`INT64`	Maximum power output in watts
`moving_time`	`INT64`	Total time spent moving during the activity
`name`	`STRING`	Name of the activity
`photo_count`	`INT64`	Total number of photos attached to the activity
`pr_count`	`INT64`	Total number of personal records achieved during the activity
`private`	`BOOL`	Indicates if the activity is private
`resource_state`	`INT64`	Resource state of the activity
`start_date`	`STRING`	Start date and time of the activity
`start_date_local`	`STRING`	Start date and time of the activity in local time
`start_latitude`	`FLOAT64`	Start latitude of the activity
`start_longitude`	`FLOAT64`	Start longitude of the activity
`timezone`	`STRING`	Timezone of the activity
`total_elevation_gain`	`FLOAT64`	Total elevation gain during the activity
`total_photo_count`	`INT64`	Total number of photos attached to the activity
`trainer`	`BOOL`	Indicates if the activity was done on a trainer
`upload_id`	`INT64`	ID of the upload associated with the activity
`upload_id_str`	`STRING`	String representation of the upload ID
`utc_offset`	`FLOAT64`	UTC offset of the activity
`visibility`	`STRING`	Visibility setting of the activity
`weighted_average_watts`	`INT64`	Weighted average power output in watts
`workout_type`	`INT64`	Type of workout (if applicable)
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: activities__end_latlng

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`value`	`FLOAT64`	End latitude and longitude coordinates of the activity
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: activities__start_latlng

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`value`	`FLOAT64`	Start latitude and longitude coordinates of the activity
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

athlete_stats (58 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`all_ride_totals__achievement_count`	`INT64`	Total number of achievements received in all rides
`all_ride_totals__count`	`INT64`	Total number of rides
`all_ride_totals__distance`	`FLOAT64`	Total distance covered in all ride activities
`all_ride_totals__elapsed_time`	`INT64`	Total elapsed time in all ride activities
`all_ride_totals__elevation_gain`	`FLOAT64`	Total elevation gain in all ride activities
`all_ride_totals__moving_time`	`INT64`	Total moving time in all ride activities
`all_run_totals__achievement_count`	`INT64`	Total number of achievements received in all runs
`all_run_totals__count`	`INT64`	Total number of runs
`all_run_totals__distance`	`FLOAT64`	Total distance covered in all run activities
`all_run_totals__elapsed_time`	`INT64`	Total elapsed time in all run activities
`all_run_totals__elevation_gain`	`FLOAT64`	Total elevation gain in all run activities
`all_run_totals__moving_time`	`INT64`	Total moving time in all run activities
`all_swim_totals__achievement_count`	`INT64`	Total number of achievements received in all swim activities
`all_swim_totals__count`	`INT64`	Total number of swims
`all_swim_totals__distance`	`FLOAT64`	Total distance covered in all swim activities
`all_swim_totals__elapsed_time`	`INT64`	Total elapsed time in all swim activities
`all_swim_totals__elevation_gain`	`FLOAT64`	Total elevation gain in all swim activities
`all_swim_totals__moving_time`	`INT64`	Total moving time in all swim activities
`biggest_climb_elevation_gain`	`FLOAT64`	Elevation gain of the biggest climb achievement
`biggest_ride_distance`	`FLOAT64`	Distance covered in the biggest ride achievement
`recent_ride_totals__achievement_count`	`INT64`	Number of achievements received in recent rides
`recent_ride_totals__count`	`INT64`	Number of recent rides
`recent_ride_totals__distance`	`FLOAT64`	Total distance covered in recent ride activities
`recent_ride_totals__elapsed_time`	`INT64`	Total elapsed time in recent ride activities
`recent_ride_totals__elevation_gain`	`FLOAT64`	Total elevation gain in recent ride activities
`recent_ride_totals__moving_time`	`INT64`	Total moving time in recent ride activities
`recent_run_totals__achievement_count`	`INT64`	Number of achievements received in recent runs
`recent_run_totals__count`	`INT64`	Number of recent runs
`recent_run_totals__distance`	`FLOAT64`	Total distance covered in recent run activities
`recent_run_totals__elapsed_time`	`INT64`	Total elapsed time in recent run activities
`recent_run_totals__elevation_gain`	`FLOAT64`	Total elevation gain in recent run activities
`recent_run_totals__moving_time`	`INT64`	Total moving time in recent run activities
`recent_swim_totals__achievement_count`	`INT64`	Number of achievements received in recent swim activities
`recent_swim_totals__count`	`INT64`	Number of recent swims
`recent_swim_totals__distance`	`FLOAT64`	Total distance covered in recent swim activities
`recent_swim_totals__elapsed_time`	`INT64`	Total elapsed time in recent swim activities
`recent_swim_totals__elevation_gain`	`FLOAT64`	Total elevation gain in recent swim activities
`recent_swim_totals__moving_time`	`INT64`	Total moving time in recent swim activities
`ytd_ride_totals__achievement_count`	`INT64`	Total number of achievements received year-to-date in ride activities
`ytd_ride_totals__count`	`INT64`	Total number of rides year-to-date
`ytd_ride_totals__distance`	`FLOAT64`	Total distance covered year-to-date in ride activities
`ytd_ride_totals__elapsed_time`	`INT64`	Total elapsed time year-to-date in ride activities
`ytd_ride_totals__elevation_gain`	`FLOAT64`	Total elevation gain year-to-date in ride activities
`ytd_ride_totals__moving_time`	`INT64`	Total moving time year-to-date in ride activities
`ytd_run_totals__achievement_count`	`INT64`	Total number of achievements received year-to-date in run activities
`ytd_run_totals__count`	`INT64`	Total number of runs year-to-date
`ytd_run_totals__distance`	`FLOAT64`	Total distance covered year-to-date in run activities
`ytd_run_totals__elapsed_time`	`INT64`	Total elapsed time year-to-date in run activities
`ytd_run_totals__elevation_gain`	`FLOAT64`	Total elevation gain year-to-date in run activities
`ytd_run_totals__moving_time`	`INT64`	Total moving time year-to-date in run activities
`ytd_swim_totals__achievement_count`	`INT64`	Total number of achievements received year-to-date in swim activities
`ytd_swim_totals__count`	`INT64`	Total number of swims year-to-date
`ytd_swim_totals__distance`	`FLOAT64`	Total distance covered year-to-date in swim activities
`ytd_swim_totals__elapsed_time`	`INT64`	Total elapsed time year-to-date in swim activities
`ytd_swim_totals__elevation_gain`	`FLOAT64`	Total elevation gain year-to-date in swim activities
`ytd_swim_totals__moving_time`	`INT64`	Total moving time year-to-date in swim activities
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

How the Strava sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Strava supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for Strava?

It depends on how much history is in your Strava account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when Strava's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in Strava, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in Strava instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the Strava connector in Kaivo and all of its synced data is deleted with it.

Common use cases for Strava data

Training volume

Use activities to track distance, moving time, and elevation by activity type and week.

Performance trends

Follow average_speed, average_watts, and heart rate across activities to see how fitness changes over time.

Activity mix

Use athlete_stats to compare ride, run, and swim totals at a glance.

Combine with other data

Join activity data with your other sources for custom reporting.

Use Strava data in your AI and BI tools

Once Strava data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with Strava data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for Strava connector pricing and plan details.

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