How does Webhook to BigQuery replication work in Kondado?

Kondado generates a unique endpoint URL that you configure in your external application or service. When events occur, your system sends JSON payloads to this endpoint, and Kondado queues, processes, and loads the data into your BigQuery destination according to your specified schedule. This reverse API approach eliminates the need for polling mechanisms while ensuring reliable data capture.

What specific data fields are available in the Post raw JSON pipeline?

The Post raw JSON pipeline includes __kdd_request_id for unique identification, __kdd_request_unix_timestamp for precise event timing, and __kdd_request_body containing the complete JSON payload. These standardized fields enable accurate event sequencing, duplicate detection, and flexible parsing of nested data structures using BigQuery's native JSON functions.

How often does Webhook data update in BigQuery?

Update frequencies are fully configurable based on your operational needs, ranging from every 5 minutes for near-real-time analytics to daily batches for cost-efficient processing. You can adjust these intervals directly within the Kondado interface without modifying your Webhook configuration or disrupting existing data flows.

Can I combine Webhook data with other data sources in BigQuery?

Absolutely. Once your Webhook data resides in BigQuery , you can join it with data from other sources such as PostgreSQL , advertising platforms, or CRM systems. This enables comprehensive cross-channel analysis and unified reporting across your entire data ecosystem.

What format is Webhook data stored in within BigQuery?

Data arrives in structured tables with JSON columns preserved in the __kdd_request_body field, allowing you to use BigQuery's JSON extraction capabilities to parse nested objects. The schema remains consistent regardless of payload variations, ensuring your SQL queries and Looker Studio connections remain stable as your data evolves.

Do I need coding skills to set up Webhook to BigQuery?

No coding is required to establish the connection or manage ongoing replication. The setup process involves copying your Kondado endpoint URL into your source application and selecting your preferred update schedule through our visual interface. Technical teams benefit from the standardized schema while analysts focus on building reports rather than data engineering.

Can I send Webhook data to multiple destinations besides BigQuery?

Yes, you can replicate the same Webhook data to additional destinations such as Google Sheets for quick sharing, PostgreSQL for transactional systems, or Power BI for specialized visualization needs. Each destination maintains independent scheduling, allowing different update frequencies for different use cases.

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Send Webhook Data to BigQuery Automatically

Setting up Webhook to BigQuery replication starts with configuring your external applications to send JSON payloads directly to your unique Kondado endpoint. Once data arrives, our platform automatically structures and loads it into your BigQuery destination, eliminating manual extraction processes and ensuring your analytics infrastructure stays current with scheduled updates. The process requires no coding knowledge, allowing technical and non-technical teams alike to establish data flows within minutes.

This pipeline operates as a reverse API connection, meaning your data source proactively pushes information to Kondado rather than waiting for scheduled pulls. You maintain complete control over update frequencies, choosing intervals that match your business requirements from 5-minute cycles to daily batches. Whether you are tracking e-commerce transactions, application events, or third-party notifications, this automated workflow ensures your data warehouse reflects the latest information without manual intervention.

Kondado provides a direct pipeline between Webhook and BigQuery that captures incoming API payloads, stores them with metadata timestamps and unique identifiers, and updates your data warehouse on a configurable schedule ranging from every 5 minutes to daily intervals.

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

Available Pipelines

The Post raw JSON pipeline captures every incoming request with complete payload data, request identifiers, and precise timestamps, enabling comprehensive event logging and debugging capabilities within your data warehouse. Once replicated to BigQuery, you can parse these JSON structures using SQL to extract specific fields, build custom attribution models, or create automated monitoring systems that alert on specific event patterns.

Marketing teams can combine this Webhook data with customer information from other sources to build unified customer journey reports in Looker Studio or Power BI, while developers use the raw logs to troubleshoot API pipelines and track system performance over time. The standardized schema ensures consistent data structure regardless of payload variations, making it ideal for high-volume event tracking and near-real-time analytics applications.

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Webhook data available for BigQuery

available pipeline

extractable fields

Available integrations

Integration	Description
Post raw JSON	This table includes fields such as __kdd_request_id, __kdd_request_unix_timestamp, and __kdd_request_body, enabling the logging of requests and their data in JSON format.

Post raw JSON

This table includes fields such as __kdd_request_id, __kdd_request_unix_timestamp, and __kdd_request_body, enabling the logging of requests and their data in JSON format.

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How to send Webhook data to BigQuery

Sync data automatically — no code, no manual exports.

Create your Webhook data source

Access the Webhook setup interface in Kondado to generate your unique endpoint URL, then configure your external application to send JSON payloads to this address.

Set up your BigQuery destination

Connect your Google Cloud project by selecting BigQuery as the target warehouse and authorizing access to your dataset where the Webhook data will be stored.

Choose pipelines and schedule updates

Select the Post raw JSON pipeline to capture complete request bodies with timestamps and identifiers, then configure your preferred replication frequency from 5-minute intervals to daily updates.

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