Amplitude connector

Set up the Amplitude connector in Kaivo: authentication, configuration, the 6 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 Amplitude 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 marketing and sales data instead of moving it.

What is the Amplitude connector

Sync your Amplitude product analytics into BigQuery with Kaivo to analyse user behaviour and engagement alongside your revenue and marketing data.

Category	Marketing & Sales, Tech
Authentication	API key
Setup	Self-service

Getting started with the Amplitude connector

Sign up for Kaivo and create a workspace.
Connect your Amplitude 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 Amplitude

Authenticate with your Amplitude credentials. You provide:

Field	Description
API Key	Your Amplitude API Key.
Secret Key	Your Amplitude Secret Key.

Configuring the Amplitude connector

When you set up the connector, you provide:

Field	Description
Data region	Select the data region for your Amplitude account.
Start Date	Any data before this date will not be fetched.

Tables and columns synced from Amplitude

Kaivo syncs 6 tables from Amplitude into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

active_users (3 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`date`	`DATE`	The date for which the active user data is reported
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

annotations (6 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`date`	`DATE`	The date when the annotation was made
`details`	`STRING`	Additional details or information related to the annotation
`id`	`INT64`	The unique identifier for the annotation
`label`	`STRING`	The label assigned to the annotation
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

average_session_length (4 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`date`	`TIMESTAMP`	The date on which the session occurred
`length`	`FLOAT64`	The duration of the session in seconds
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

cohorts (23 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`app_id`	`INT64`	The unique identifier of the application.
`archived`	`BOOL`	Indicates if the cohort data is archived or not.
`description`	`STRING`	A brief explanation or summary of the cohort data.
`finished`	`BOOL`	Indicates if the cohort data has been finalized.
`id`	`STRING`	The unique identifier for the cohort.
`name`	`STRING`	The name or title of the cohort.
`published`	`BOOL`	Status indicating if the cohort data is published or not.
`size`	`INT64`	Size or scale of the cohort data.
`type`	`STRING`	The type or category of the cohort.
`last_mod`	`INT64`	Timestamp of the last modification made to the cohort.
`last_computed`	`INT64`	Timestamp of the last computation of cohort data.
`hidden`	`BOOL`	Flag to determine if the cohort is hidden from view.
`is_predictive`	`BOOL`	Flag to indicate if the cohort is predictive in nature.
`is_official_content`	`BOOL`	Indicates if the cohort data is official content.
`chart_id`	`STRING`	The identifier of the chart associated with the cohort.
`created_at`	`INT64`	The timestamp when the cohort was created.
`edit_id`	`STRING`	The ID for editing purposes or version control.
`last_viewed`	`INT64`	Timestamp when the cohort was last viewed.
`location_id`	`STRING`	Identifier of the location associated with the cohort.
`popularity`	`INT64`	Popularity rank or score of the cohort.
`view_count`	`INT64`	The total count of views on the cohort data.
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: cohorts__owners

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`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: cohorts__metadata

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`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: cohorts__shortcut_ids

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`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: cohorts__viewers

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`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

events (53 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`server_received_time`	`TIMESTAMP`	The timestamp when the event data was received by the server
`app`	`INT64`	Information related to the application where the event originated
`device_carrier`	`STRING`	The mobile carrier used by the device
`_schema`	`INT64`	The schema version used for the event data
`city`	`STRING`	The city where the event occurred
`user_id`	`STRING`	The unique identifier for the user
`uuid`	`STRING`	The universally unique identifier for the event
`event_time`	`TIMESTAMP`	The timestamp when the event occurred
`platform`	`STRING`	The platform where the event occurred (e.g., iOS, Android)
`os_version`	`STRING`	The version of the operating system on the user's device
`amplitude_id`	`INT64`	The unique identifier assigned by Amplitude for the event
`processed_time`	`TIMESTAMP`	The timestamp when the event data was processed
`user_creation_time`	`TIMESTAMP`	The timestamp when the user account was created
`version_name`	`STRING`	The name or label of the version associated with the event
`ip_address`	`STRING`	The IP address from which the event was triggered
`paying`	`BOOL`	Flag indicating if the user is a paying customer
`dma`	`STRING`	The Designated Market Area where the event occurred
`client_upload_time`	`TIMESTAMP`	The timestamp when the event data was uploaded from the client to the server
`_insert_id`	`STRING`	The unique identifier assigned by Amplitude for each event insertion
`event_type`	`STRING`	The type/category of the event
`library`	`STRING`	Information about the library/version used for event tracking
`amplitude_attribution_ids`	`STRING`	IDs that Amplitude uses for attributing conversions to various ad networks
`device_type`	`STRING`	The type of device (e.g., smartphone, tablet)
`device_manufacturer`	`STRING`	The manufacturer of the device
`start_version`	`STRING`	The version at which the user started using the application
`location_lng`	`FLOAT64`	Longitude coordinate of the event location
`server_upload_time`	`TIMESTAMP`	The timestamp when the event data was uploaded to the server
`event_id`	`INT64`	The unique identifier assigned to the event
`location_lat`	`FLOAT64`	Latitude coordinate of the event location
`os_name`	`STRING`	The name of the operating system on the user's device
`amplitude_event_type`	`STRING`	The specific type of event tracked by Amplitude
`device_brand`	`STRING`	The brand of the user's device
`device_id`	`STRING`	The unique identifier assigned to the device
`language`	`STRING`	The language set on the user's device
`device_model`	`STRING`	The model of the device
`country`	`STRING`	The country where the event occurred
`region`	`STRING`	The region where the event occurred
`is_attribution_event`	`BOOL`	Flag indicating if the event is an attribution event
`adid`	`STRING`	The advertising identifier associated with the user's device
`session_id`	`FLOAT64`	The unique identifier for the user session
`device_family`	`STRING`	The family of the device model
`sample_rate`	`STRING`	The sampling rate used for the event data
`idfa`	`STRING`	The Identifier for Advertisers associated with the user's device
`client_event_time`	`TIMESTAMP`	The timestamp when the event occurred on the client side
`_insert_key`	`STRING`	The key used for identifying the event insertion
`data_type`	`STRING`	The type of data associated with the event
`plan__branch`	`STRING`	The branch of the user's plan
`plan__source`	`STRING`	The source of the user's plan
`plan__version`	`STRING`	The version of the user's plan
`source_id`	`STRING`	The unique identifier for the event source
`partner_id`	`STRING`	The unique identifier for a partner associated with the event
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

events_list (16 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`autohidden`	`BOOL`
`clusters_hidden`	`BOOL`
`deleted`	`BOOL`
`display`	`STRING`
`flow_hidden`	`BOOL`
`hidden`	`BOOL`
`id`	`FLOAT64`
`in_waitroom`	`BOOL`
`name`	`STRING`
`non_active`	`BOOL`
`timeline_hidden`	`FLOAT64`
`totals`	`FLOAT64`
`totals_delta`	`FLOAT64`
`value`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

How the Amplitude sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Amplitude 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 Amplitude?

It depends on how much history is in your Amplitude 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 Amplitude'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 Amplitude, 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 Amplitude 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 Amplitude connector in Kaivo and all of its synced data is deleted with it.

Common use cases for Amplitude data

Engagement trends

Use active_users and average_session_length to track how engagement changes over time and after releases.

Funnel and retention

Analyse the events and cohorts data to measure activation, retention, and where users drop off.

Feature adoption

Break events down by type to see which features get used and by whom.

Product and revenue together

Join Amplitude events with billing data in BigQuery to connect product usage to expansion and churn.

Use Amplitude data in your AI and BI tools

Once Amplitude 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 Amplitude 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 Amplitude connector pricing and plan details.

Google Ads: Sync Google Ads to BigQuery.
Custobar: Sync Custobar to BigQuery.
Google Search Console: Sync Google Search Console to BigQuery.
HubSpot: Sync HubSpot to BigQuery.
Adform: Sync Adform to BigQuery.
Auth0: Sync Auth0 to BigQuery.

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