Send data from BigQuery to PostgreSQL

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Send BigQuery Data to PostgreSQL Automatically

Kondado provides direct integration between BigQuery and PostgreSQL without requiring code or complex engineering. Users configure which tables and views to replicate from their BigQuery data source through an intuitive web interface that handles authentication and schema mapping automatically. Data arrives in your PostgreSQL destination on a configurable schedule: every 5 minutes, hourly, or daily, depending on your specific business requirements and latency needs. This automated pipeline eliminates tedious manual CSV exports, fragile custom scripts, and the engineering overhead typically required to maintain data synchronization between Google Cloud and open-source databases.

Once your BigQuery data lands in PostgreSQL, analysts can leverage advanced SQL capabilities to run complex queries, build custom reports, or feed cleansed data into visualization tools like Power BI and Looker Studio. The replication process preserves your existing data structure and relationships while making Google Cloud datasets accessible in an open-source environment optimized for high-performance analytical workloads and cost-effective storage.

Kondado automatically replicates your BigQuery tables and views to PostgreSQL on a configurable schedule, enabling you to analyze Google Cloud data using PostgreSQL’s advanced query capabilities without manual exports or engineering resources.

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

Available BigQuery to PostgreSQL Pipelines

The Tabelas pipeline automatically maps and replicates your BigQuery database tables to PostgreSQL, bringing raw event data, transaction records, and user analytics into an environment where you can perform advanced joins and transformations. This enables you to combine BigQuery’s data warehouse capabilities with PostgreSQL’s robust querying engine for deeper operational insights.

The Views pipeline handles your BigQuery virtual tables, replicating pre-calculated metrics and business logic directly into PostgreSQL. Once replicated, these views serve as ready-to-query datasets for building custom dashboards in Power BI or Looker Studio, or for feeding downstream applications that require structured analytical outputs on a configurable schedule.

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Dynamic data

Kondado automatically reads the schema of your BigQuery. All tables, views, and fields available in your account are extracted without manual configuration.

1
available pipeline

What Kondado extracts

Tabelas e Views
Kondado automatically maps all tables and views available in your database
Integration Description
Tabelas e Views Kondado automatically maps all tables and views available in your database
See all available data →

Try out all the features for free for 14 days

How to send BigQuery data to PostgreSQL

Sync data automatically — no code, no manual exports.

1
Connect BigQuery Source

Authenticate your Google Cloud project in Kondado by providing service account credentials, then select the specific BigQuery datasets you want to replicate to PostgreSQL.

2
Configure PostgreSQL Destination

Enter your PostgreSQL connection details including host, database name, and credentials to establish the target location where your BigQuery tables and views will land.

3
Select Data and Schedule

Choose which tables and views to replicate from your BigQuery data source and define your update frequency, whether every 5 minutes for frequent refreshes or daily for batch processing.

Try out all the features for free for 14 days

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With the same platform, you send data to reports, spreadsheets, databases, data warehouses, and data lakes. ETL and ELT

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Send data from BigQuery to other destinations

Looker Studio

BigQuery > Looker Studio
Power BI

BigQuery > Power BI
Other visualizations
Other visualizations
Amazon S3

BigQuery > Amazon S3
BigQuery

BigQuery > BigQuery
Excel

BigQuery > Excel
Google Sheets

BigQuery > Google Sheets
MySQL

BigQuery > MySQL
PostgreSQL

BigQuery > PostgreSQL
Redshift

BigQuery > Redshift
SQL Server

BigQuery > SQL Server

Choose a tool to visualize your BigQuery data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Airtable
BigQuery > Airtable
Alteryx
BigQuery > Alteryx
Amazon Quicksight
BigQuery > Amazon Quicksight
BIMachine
BigQuery > BIMachine
Cortex
BigQuery > Cortex
Data Studio
BigQuery > Data Studio
Geckoboard
BigQuery > Geckoboard
Grafana
BigQuery > Grafana
IBM Cognos Analytics
BigQuery > IBM Cognos Analytics
Klipfolio
BigQuery > Klipfolio
Looker Studio
BigQuery > Looker Studio
Looker
BigQuery > Looker
Looqbox
BigQuery > Looqbox
Metabase
BigQuery > Metabase
Microstrategy
BigQuery > Microstrategy
Pentaho
BigQuery > Pentaho
Power BI
BigQuery > Power BI
Qlik Cloud Analytics
BigQuery > Qlik Cloud Analytics
Qlik Sense
BigQuery > Qlik Sense
Qlik
BigQuery > Qlik
QlikView
BigQuery > QlikView
Redash
BigQuery > Redash
Superset
BigQuery > Superset
Tableau
BigQuery > Tableau
BI TOTVS
BigQuery > BI TOTVS
Zoho Analytics
BigQuery > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending BigQuery data to PostgreSQL automatically

How does Kondado replicate BigQuery data to PostgreSQL without coding? ▼
Kondado uses a direct integration that connects to your BigQuery project through authenticated APIs, then automatically maps your selected tables and views to corresponding structures in PostgreSQL. You configure the connection through a visual interface where you select specific datasets and set your preferred update schedule. The platform handles schema conversion, data type mapping, and the actual data transfer without requiring SQL scripts, Python code, or manual CSV handling.
What specific BigQuery objects can I replicate to PostgreSQL? ▼
Kondado's pipeline supports replicating both standard tables and views from your BigQuery data source, including partitioned tables and nested data structures commonly found in Google Analytics exports. You can select specific datasets or choose individual tables and views based on your analytical needs. The system preserves your BigQuery schema relationships while converting data types to their PostgreSQL equivalents for seamless querying.
How often can I update BigQuery data in my PostgreSQL database? ▼
Kondado offers flexible scheduling options ranging from every 5 minutes for near-real-time operational analytics to hourly or daily batches for cost-efficient historical analysis. You configure the frequency per pipeline based on your data freshness requirements and BigQuery query costs. Each update automatically refreshes your PostgreSQL tables with the latest data from Google Cloud without manual intervention.
Does BigQuery data maintain its structure when replicated to PostgreSQL? ▼
Yes, Kondado preserves your original BigQuery schema including column names, data types, and table relationships during the replication process, converting Google Cloud data types to appropriate PostgreSQL equivalents. Nested and repeated fields from BigQuery are flattened or structured according to your configuration preferences. This structural integrity ensures your existing SQL queries and Power BI reports continue functioning correctly after migration.
Can I combine BigQuery data with other sources in the same PostgreSQL database? ▼
Absolutely, you can replicate data from over 80 additional sources including Google Sheets, marketing platforms, and CRM systems into the same PostgreSQL instance alongside your BigQuery tables. This enables cross-source analysis using PostgreSQL's join capabilities, allowing you to enrich BigQuery analytics with external business data. Create unified reports that blend Google Cloud warehouse data with operational systems for comprehensive business intelligence.
What happens to my PostgreSQL reports when BigQuery data updates? ▼
When Kondado updates your BigQuery data on the configured schedule, all dependent reports, dashboards, and SQL queries in your PostgreSQL environment automatically reflect the new information. If you connect PostgreSQL to Looker Studio or other BI tools, those visualizations refresh with the latest data without requiring manual updates. This automation ensures your analytics stay current with your Google Cloud data warehouse on a timeline you control.
Is it possible to replicate specific BigQuery views rather than entire datasets? ▼
Yes, Kondado allows you to select individual views from your BigQuery project, replicating only the pre-filtered, calculated datasets you need for specific analytical purposes. This selective replication reduces unnecessary data transfer and storage costs in PostgreSQL while bringing over complex SQL logic already defined in BigQuery. You can maintain different view pipelines with varying update frequencies based on business criticality.

Try out all the features for free for 14 days