No-code pipeline · BigQuery → Amazon S3

Send data from BigQuery to Amazon S3

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

From BigQuery to Amazon S3: managed, scheduled, no code.

Kondado automatically replicates BigQuery tables and views to Amazon S3 on a configurable schedule ranging from every 5 minutes to daily, enabling seamless data lake architecture and compatibility with Athena, Presto, and Dremio analytics tools.

Connect BigQuery now →

Replicate BigQuery Data to Amazon S3 Automatically

How to send BigQuery data to Amazon S3? Kondado provides a direct integration that connects your Google BigQuery data source to Amazon S3 without requiring any coding. You simply authenticate your BigQuery account, configure your S3 bucket as the destination, and select which database objects you want to replicate. The platform handles the data transfer on a configurable schedule, ensuring your S3 bucket always contains the latest information from your Google Cloud data warehouse.

This pipeline eliminates manual exports and complex ETL scripting, allowing data teams to focus on analysis rather than data movement. Whether you need to archive historical data, feed analytics engines, or combine BigQuery information with other sources in your S3 data lake, Kondado streamlines the process with automated updates and consistent data formatting.

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

Through the Tables and Views pipeline, Kondado automatically maps and replicates all your BigQuery database objects to Amazon S3, including complex views and multi-table datasets. This enables you to query unified datasets using Amazon Athena or join BigQuery exports with other business data already stored in your S3 buckets.

Agencies can leverage this replicated data to build custom dashboards by connecting business intelligence tools directly to the S3 files, while technical teams can process the information through Presto or Dremio for advanced virtualization and cross-platform analytics without maintaining complex data pipelines manually.

Try out all the features for free for 14 days

Replicated to Amazon S3

Dynamic data

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

available pipeline

Amazon S3

Destination

What Kondado extracts

Tabelas e Views

Kondado automatically maps all tables and views available in your database

See all available data → Send BigQuery to Amazon S3 →

Try out all the features for free for 14 days

How to send BigQuery data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect Your BigQuery Account

Authenticate your Google Cloud credentials and select the BigQuery project containing the datasets you want to replicate to Amazon S3.

Configure Amazon S3 Bucket

Enter your AWS access details and specify the destination S3 bucket where your data will be stored for analysis in Power BI, Athena, or other tools.

Select Objects and Schedule

Choose which tables and views to replicate from your BigQuery data source and set your automated update frequency ranging from every 5 minutes to daily intervals.

Try out all the features for free for 14 days

Hundreds of data-driven companies trust Kondado

Why Kondado?

Focus on extracting value from your data and leave the rest to us

Wherever you need

With the same platform, you send data to AI (Claude/ChatGPT via MCP), reports, spreadsheets, databases, data warehouses, and data lakes. ETL and ELT

Learn More About Our Platform →

From wherever you need

Data from over 80 sources for Marketing, Ecommerce, ERPs, Customer Service, Finance, Databases, and much more

Learn More About Our Data Sources →

Predictable pricing

No surprise invoices, pick a plan and change it anytime

Check out our plans →

Send data from BigQuery to other destinations

BigQuery > Looker Studio

BigQuery > Power BI

Other visualizations

BigQuery > Amazon S3

BigQuery > BigQuery

BigQuery > Excel

BigQuery > Google Sheets

BigQuery > MySQL

BigQuery > PostgreSQL

BigQuery > Redshift

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

BigQuery > Airtable

BigQuery > Alteryx

BigQuery > Amazon Quicksight

BigQuery > BIMachine

BigQuery > Cortex

BigQuery > Data Studio

BigQuery > Geckoboard

BigQuery > Grafana

BigQuery > IBM Cognos Analytics

BigQuery > Klipfolio

BigQuery > Looker Studio

BigQuery > Looker

BigQuery > Looqbox

BigQuery > Metabase

BigQuery > Microstrategy

BigQuery > Pentaho

BigQuery > Power BI

BigQuery > Qlik Cloud Analytics

BigQuery > Qlik Sense

BigQuery > Qlik

BigQuery > QlikView

BigQuery > Redash

BigQuery > Superset

BigQuery > Tableau

BigQuery > BI TOTVS

BigQuery > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending BigQuery data to Amazon S3 automatically

How does Kondado replicate BigQuery data to Amazon S3? ▼

Kondado establishes a direct connection to your BigQuery data source and automatically extracts your selected database objects. The platform then loads this data into your specified Amazon S3 bucket on your chosen schedule, maintaining data consistency and structure throughout the transfer process.

What BigQuery objects can I replicate to Amazon S3? ▼

You can replicate both tables and views from your BigQuery datasets through the available pipeline. Kondado automatically maps all available database objects, allowing you to select specific datasets or replicate entire schemas depending on your data lake requirements.

How often does BigQuery data update in Amazon S3? ▼

Updates occur on a configurable schedule that you set during pipeline configuration, with options ranging from every 5 minutes to daily intervals. This ensures your Amazon S3 buckets contain near-real-time information for time-sensitive analytics or historical archives for long-term storage.

What file format does BigQuery data arrive in Amazon S3? ▼

Data arrives in structured formats optimized for analytics engines like Athena, Presto, and Dremio, typically as compressed columnar files. This format enables efficient querying and processing directly within your S3 environment without additional transformation steps.

Can I combine BigQuery data with other sources in Amazon S3? ▼

Yes, you can replicate data from multiple sources into the same S3 bucket to create unified data lakes. Combine your BigQuery exports with information from PostgreSQL or other platforms, then query everything together using Amazon Athena or feed the consolidated datasets into Power BI for comprehensive reporting.

Do I need coding skills to send BigQuery data to Amazon S3? ▼

No coding is required to configure this pipeline, as Kondado provides a no-code interface for connecting your BigQuery data source and Amazon S3 destination. Simply authenticate both services, select your data, and set your schedule through the visual pipeline builder.

Can I use BigQuery data in Amazon S3 with Athena and Presto? ▼

Absolutely, data replicated from BigQuery to Amazon S3 is immediately compatible with Athena, Presto, and Dremio for serverless querying. This architecture separates your storage from compute resources, allowing you to analyze BigQuery exports using AWS-native tools or external virtualization layers.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days