Stream into Google GCS Parquet with your free account

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

<100ms to batch
200+ connectors
Managed data pipelines

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01. Select a source02. Transform in-flight03. Deliver to Google GCS Parquet

Google GCS Parquet connector details

The Google Cloud Storage Parquet materialization connector in Estuary writes delta updates from Estuary collections into Apache Parquet files in a Google Cloud Storage bucket. Updates are batched within Estuary, converted to Parquet, and uploaded to GCS at a configurable interval for analytics, data lake, and downstream processing workloads.

Materializes delta updates from Estuary collections as Apache Parquet files
Configurable upload interval, with a default of 5 minutes
Configurable file-size limit, defaulting to approximately 10 GiB
Configurable row group size, including row-count and byte-size limits
Optional GCS object prefix for organizing materialized files
Configurable destination path for each Estuary collection
Automatic mapping of Estuary data types to Parquet data types
Google Cloud service account authentication
Requires **roles/storage.objectCreator** permission on the destination bucket

Each Estuary collection produces a sequence of separate .parquet files rather than one continuously updated file. Files use monotonically increasing, zero-padded names so they remain lexicographically sortable, and a new version path is created when a binding is re-backfilled.

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

How to connect your data source to Google GCS Parquet 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 GCS Parquet
Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

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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 GCS Parquet, 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 GCS Parquet through Estuary.
Transform and route data through Estuary collections before delivering it to Google GCS Parquet.

See what you can connect to Google GCS Parquet:

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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