Stream into Google Bigquery with your free account

Deliver data from databases, SaaS apps, APIs, files, and streaming systems into Google Bigquery using Estuary's pre-built connectors. Run pipelines from real-time streaming to scheduled batch based on connector capabilities.

<100ms to batch
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01. Select a source02. Transform in-flight03. Deliver to Google Bigquery

Google Bigquery connector details

Estuary’s Google BigQuery materialization connector writes Estuary collections into tables within a BigQuery dataset for scalable analytics and near real-time reporting. The connector stages data through Google Cloud Storage, then applies standard merges or high-speed delta updates so BigQuery stays current as upstream data changes.

Materialize Estuary collections into BigQuery tables within a selected BigQuery dataset.
Use a Google Cloud Storage bucket as a temporary staging area for reliable delivery into BigQuery.
Create the staging bucket in the same region as the destination BigQuery dataset.
Support both standard merge mode and delta update mode for performance and update flexibility.
Use a Google Cloud service account with access to the BigQuery dataset, BigQuery jobs, BigQuery read sessions, and the staging GCS bucket.
Enable clustering by primary keys where appropriate to improve query performance on materialized tables.

See how Cosuno uses Google Bigquery

For more details about the Google Bigquery connector, check out the documentation page.

How to connect your data source to Google Bigquery in 3 easy steps

1
Connect your data source
Select from more than 100 supported databases and SaaS platforms including PostgreSQL, MySQL, SQL Server, MongoDB, and Kafka.
2
Prepare and transform your data
Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.
3
Sync to Google Bigquery
Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

Learn more

Dive deeper into Google Bigquery with this quick video from our YouTube channel.

Google BigQuery Explained in 3 Minutes: An Overview
BigQuery is Google's fully managed, serverless data warehouse that enables scalable analysis over petabytes of data.

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HIGH THROUGHPUT

Distributed, event-driven architecture scales for demanding data workloads.

DURABLE COLLECTIONS

Store data as it moves so you can transform, replay, and deliver it downstream.

FLEXIBLE LATENCY

From <100ms CDC and real-time streaming to scheduled batch, depending on connector capabilities.

From <100ms to batch

Estuary supports CDC, real-time streaming, incremental syncs, and scheduled batch across its connector ecosystem. Bring data from databases, SaaS apps, APIs, files, and event streams into Google Bigquery, with capture and delivery cadence based on connector capabilities and pipeline configuration.

Connect data from operational databases, SaaS applications, APIs, files, and streaming systems to Google Bigquery through Estuary.
Transform and route data through Estuary collections before delivering it to Google Bigquery.

See what you can connect to Google Bigquery:

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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.

Feature Comparison

	Estuary	Batch ELT/ETL	DIY Python	Kafka
Price	$	$$-$$$$	$-$$$$	$-$$$$
Latency	<100ms to scheduled	5min+	Varies	<100ms
Ease	Analysts can manage	Analysts can manage	Data Engineer	Senior Data Engineer
Scale
Maintenance Effort	Low	Medium	High	High