How does Kondado replicate Pagar.me data to BigQuery?

Kondado establishes a direct connection to your Pagar.me account and extracts data from your selected pipelines. The platform then loads this information into your BigQuery dataset on your configured schedule, handling all data type mapping and schema management automatically. You maintain full control over which data endpoints sync and how frequently they refresh.

What Pagar.me data can I replicate to BigQuery?

You can replicate eight distinct pipelines including Customers, Charges, Orders, Receivables, Balance Operations, and card details. These cover transaction amounts, payment statuses, customer contact information, and recipient data across 344 available fields. This comprehensive coverage supports detailed financial analysis and customer behavior tracking.

How frequently can I update Pagar.me data in BigQuery?

Kondado offers configurable update schedules ranging from every five minutes to daily intervals, depending on your analytics requirements. You can set different frequencies for each pipeline, ensuring high-volume transaction data refreshes faster than static customer records. This keeps your BigQuery datasets current without overwhelming your data warehouse.

Can I combine Pagar.me data with ecommerce platforms in BigQuery?

Yes, you can replicate data from Pagar.me alongside other sources connected to BigQuery such as ecommerce tools and advertising platforms. This enables you to correlate payment transactions with website traffic, inventory levels, and marketing campaigns using SQL joins. The combined datasets support unified reporting across your entire sales funnel.

What data types does Pagar.me use in BigQuery?

Kondado preserves Pagar.me's original data types including timestamps for transaction dates, numeric fields for amounts, and strings for customer identifiers. The platform automatically handles currency conversions and null values to ensure your BigQuery queries return accurate results. Standardized schemas make it easy to connect your data to Looker Studio or Power BI .

Do I need technical skills to send Pagar.me data to BigQuery?

No coding is required to establish the connection between Pagar.me and BigQuery . The interface guides you through authenticating your Pagar.me account and selecting your desired pipelines without writing SQL or API calls. Once configured, the automated replication runs continuously in the background.

Which pipelines contain Pagar.me customer payment methods?

The Customers: Cards pipeline specifically stores card brand, expiration dates, and masked digits, while the main Customers pipeline contains contact and address information. You can replicate these separately to analyze payment method preferences or combine them for complete customer profiles in BigQuery .

Send data from Pagar.me to BigQuery

Get started for free

No credit card required | 14 days | 10 million records | 30 pipelines

or sign up with your email

By signing up, you agree to Kondado’s Terms of service and Privacy policy

Send Pagar.me Data to BigQuery Automatically

Kondado provides a direct integration between Pagar.me and BigQuery that replicates your payment data on a configurable schedule. You select which pipelines you need from the eight available data endpoints, including Customers, Charges, and Orders, and define how frequently the data should refresh. The platform handles the data extraction and loading automatically, requiring no code or technical maintenance from your team.

Once connected, your Pagar.me financial information flows directly into your Google Cloud data warehouse, ready for complex querying and business intelligence. Analysts can combine transaction data with other sources to build comprehensive revenue reports and automate financial monitoring without manual CSV exports.

Kondado automatically replicates Pagar.me data to BigQuery on a configurable schedule, offering eight pipelines with 344 fields including Customers, Charges, Orders, and Receivables, enabling automated financial analytics without coding.

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

The Customers pipeline delivers detailed buyer information including contact details and addresses, enabling you to segment your audience and analyze purchasing patterns directly in BigQuery. By combining the Charges and Receivables pipelines, finance teams can create automated cash flow monitoring, reconcile pending payments against completed transactions, and generate accurate revenue forecasts using SQL queries. These datasets integrate seamlessly with your existing business intelligence workflows, allowing you to build custom dashboards that track conversion rates, payment success metrics, and customer lifetime value without manual data preparation.

Try out all the features for free for 14 days

Pagar.me data available for BigQuery

available pipelines

344

extractable fields

Available integrations

Integration	Description
Customers	Includes information such as customer name, email, and status, along with address and phone data like area code and number.
Customers: Cards	Records card details including brand, expiration date, and status, along with cardholder name and card digits.
Customers: Addresses	Contains address data such as city, state, and country, along with creation date and address status.
Charges	Includes information on charges made, such as amount, date, and status, along with details of the associated customer.
Balance Operations	Records operations related to balance, including operation type, amount, and transaction date.
Orders	Contains details of orders placed, such as total amount, status, and creation date, along with customer information.
Recipients	Includes information about recipients, such as name, document, and status, along with creation and update data.
Receivables	Contains information about receivables, including amount, due date, and status, along with details of the associated customer.

Customers

Includes information such as customer name, email, and status, along with address and phone data like area code and number.

Customers: Cards

Records card details including brand, expiration date, and status, along with cardholder name and card digits.

Customers: Addresses

Contains address data such as city, state, and country, along with creation date and address status.

Charges

Includes information on charges made, such as amount, date, and status, along with details of the associated customer.

Balance Operations

Records operations related to balance, including operation type, amount, and transaction date.

Orders

Contains details of orders placed, such as total amount, status, and creation date, along with customer information.

Recipients

Includes information about recipients, such as name, document, and status, along with creation and update data.

Receivables

Contains information about receivables, including amount, due date, and status, along with details of the associated customer.

See all available data →

Try out all the features for free for 14 days

How to send Pagar.me data to BigQuery

Sync data automatically — no code, no manual exports.

Connect Your Pagar.me Account

Authenticate your Pagar.me credentials in Kondado to establish the data source connection and enable access to your payment transactions.

Configure BigQuery Destination

Set up your BigQuery project and dataset details in Kondado, specifying where your Pagar.me data should load within your Google Cloud environment.

Select Pipelines and Schedule

Choose from the eight available Pagar.me pipelines such as Charges and Customers, then configure your preferred update frequency to automate data replication into BigQuery.

Try out all the features for free for 14 days