How does the Toggl to BigQuery replication work?

Kondado connects directly to the Toggl API to extract your time tracking data and loads it into your BigQuery dataset automatically. You select which pipelines to enable, such as Time Entries or Projects, and the system handles the schema creation and data loading on your chosen schedule. The process requires no manual exports, CSV uploads, or maintenance of custom scripts.

What Toggl data can I replicate to BigQuery?

Kondado offers 10 distinct pipelines covering Clients, Groups, Projects, Tasks, Time Entries, Workspaces, and their relationships. Each pipeline contains specific fields, such as duration in seconds for Time Entries or hourly rates for Projects: Users, giving you granular access to time tracking metrics. You can enable all pipelines or select only those relevant to your analysis needs.

How often does Toggl data update in BigQuery?

You configure the update frequency based on your business needs, with options ranging from every 5 minutes to daily intervals. This near-real-time capability ensures your reports reflect recent time entries without overwhelming your API limits or BigQuery storage costs. The schedule runs automatically once set, keeping your analytics current.

Can I combine Toggl data with other sources in BigQuery?

Yes, once your Toggl data resides in BigQuery , you can join it with data from other platforms or business applications. Many users combine time tracking data with financial information from accounting software or CRM data to calculate true project costs and ROI. BigQuery's SQL capabilities enable complex joins across all your replicated datasets.

What format does Toggl data take in BigQuery?

Each Toggl pipeline becomes a separate dataset in BigQuery with properly typed columns matching the original API fields. Time Entries include timestamps and duration integers, while Projects contain currency fields for rates and status indicators. Kondado maintains consistent schema structures so your SQL queries remain stable across data refreshes.

Do I need coding skills to connect Toggl to BigQuery?

No coding is required to establish the connection or maintain data flows. The interface guides you through authenticating your Toggl data source and selecting your BigQuery destination using point-and-click configuration. Technical teams can focus on writing analytics queries rather than building and maintaining extraction pipelines.

Can I track project profitability with Toggl data in BigQuery?

Absolutely, by combining the Projects and Projects: Users pipelines, you can calculate labor costs using stored hourly rates and actual hours worked. Join this data with your revenue figures to determine margins, identify which clients generate the most profit per hour, and optimize your team's billable rate strategies. These custom calculations provide insights unavailable in standard Toggl reports.

How do I analyze Toggl time entries alongside financial data?

Once replicated to BigQuery , your Time Entries data can be joined with accounting or ERP datasets using project IDs or client identifiers. Create unified dashboards in Looker Studio or Power BI that correlate hours worked with invoices paid, revealing cash flow patterns and resource utilization. This unified view eliminates the data silos between operations and finance teams.

Send data from Toggl to BigQuery

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Send Toggl Data to BigQuery Automatically

Kondado provides a direct integration between Toggl and BigQuery that eliminates manual data exports and complex API coding. You simply authenticate your Toggl account, select which pipelines you want to replicate from the available options, and configure your preferred update schedule. The platform handles the data extraction, transformation, and loading into your BigQuery warehouse automatically, requiring no technical expertise or maintenance.

Once configured, your time tracking data flows into BigQuery on a configurable schedule, enabling you to analyze work hours, project profitability, and team productivity alongside other business data. This automated pipeline ensures your analytics always reflect the latest time entries without requiring manual intervention, allowing you to build comprehensive reports in Looker Studio or other analytics tools.

Kondado replicates Toggl data to BigQuery through 10 available pipelines including Time Entries, Projects, and Workspaces, updating on a configurable schedule ranging from every 5 minutes to daily, with no coding required.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Toggl Pipelines for BigQuery

The available pipelines cover every aspect of your time tracking operations, from detailed Time Entries showing exact durations and descriptions to Projects data revealing actual hours and billing rates. You can analyze the Projects: Users pipeline to calculate labor costs and profitability per team member, or examine Workspaces data to compare productivity across different organizational units.

With this data in BigQuery, you can create custom dashboards tracking billable hours by client, identify which projects consume the most resources, or calculate accurate project margins by combining labor costs with revenue data. These insights enable data-driven decisions about resource allocation, pricing strategies, and team capacity planning.

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Toggl data available for BigQuery

available pipelines

141

extractable fields

Available integrations

Integration	Description
Clients	Includes fields such as client ID, name, and workspace ID, enabling efficient client management.
Groups	Contains information about group ID, name, and list of workspaces, facilitating project organization.
Projects	Presents data such as project ID, actual hours, status, and hourly rate, essential for tracking activities.
Projects: Groups	Includes unique identifiers for projects and groups, facilitating the association between them.
Projects: Users	Provides data such as user ID, labour cost, and hourly rate, allowing analysis of user performance in projects.
Tags	Contains information about tag ID, name, and workspace ID, facilitating the categorization of entries.
Tasks	Includes data such as task ID, status, and update timestamp, aiding in activity management.
Time Entries	Presents information such as entry ID, description, and duration in seconds, essential for time tracking.
Workspaces	Contains data about workspace ID and name, allowing for the organization of projects and teams.
Workspaces: Users	Includes information such as user ID, name, and workspace ID, facilitating user management across different workspaces.

Clients

Includes fields such as client ID, name, and workspace ID, enabling efficient client management.

Groups

Contains information about group ID, name, and list of workspaces, facilitating project organization.

Projects

Presents data such as project ID, actual hours, status, and hourly rate, essential for tracking activities.

Projects: Groups

Includes unique identifiers for projects and groups, facilitating the association between them.

Projects: Users

Provides data such as user ID, labour cost, and hourly rate, allowing analysis of user performance in projects.

How to send Toggl data to BigQuery

Sync data automatically — no code, no manual exports.

Connect Your Toggl Data Source

Authenticate your Toggl workspace in Kondado by providing your API credentials through the secure connection interface. The system validates your access and retrieves the available pipelines from your time tracking account.

Configure BigQuery Destination

Select your BigQuery project and dataset where the Toggl data will be stored, specifying the region and dataset structure. Kondado creates the necessary schema automatically based on the pipelines you choose to enable.

Select Pipelines and Schedule

Choose which data pipelines to replicate, such as Time Entries or Projects, and set your preferred update frequency from 5 minutes to daily. Once activated, Kondado begins the initial data load and maintains automated updates according to your configuration.

Try out all the features for free for 14 days