Stream data from Zuora to Google Bigquery
Move data from Zuora to Google Bigquery in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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How to integrate Zuora with Google Bigquery
- 1
Connect Zuora as your data source
Set up a source connector for Zuora in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
- 2
Create GCP resources
Your Google BigQuery materialization will need: a storage bucket, a BigQuery dataset to use, and a service account with access to both.
- 3
Create a Bigquery materialization in Estuary
Provide details about your new GCP resources, your GCP project ID, and your region.
- 4
Customize your integration
Optionally set up a sync schedule (defaults to 30 minutes if unset) for faster or slower data syncs, job triggers, and more.
- 5
Connect collections and publish
Data collections are then materialized into new tables within your BigQuery dataset.
Zuora connector details
The Zuora capture connector in Estuary captures billing and subscription data from Zuora through the AQuA API and loads each selected object into an Estuary collection. The connector automatically discovers the Zuora objects available to your account and chooses the appropriate replication method based on each object’s fields.
- API-based data capture through Zuora’s AQuA API
- Automatic discovery of standard and custom Zuora objects available to your account
- Incremental replication for objects with an
UpdatedDatefield, capturing only new and changed records after the initial backfill - Full-refresh snapshots for objects that do not support
UpdatedDatebased incremental capture - Supports core billing objects such as Accounts, Subscriptions, Invoices, Payments, Products, and Rate Plans
- Support for custom Zuora objects exposed through your account
- Configurable sync intervals, with a default interval of 5 minutes
- Configurable start date for historical replication, defaulting to January 1, 2007
- OAuth 2.0 client credentials authentication
For objects that expose an UpdatedDate field, Estuary uses it as a cursor so that subsequent syncs retrieve only new or modified records. Objects without an UpdatedDate field are re-captured as full snapshots during each polling interval.
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
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Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.
Zuora to Google Bigquery pricing estimate
Estimated monthly cost to move 800 GB from Zuora to Google Bigquery is approximately $1,000.
Data moved
Choose how much data you want to move from Zuora to Google Bigquery each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.
What customers are saying
Estuary just works. We’ve never had an incident, and it cut our data movement costs in half.
Read the Success Story
We're a big fan of Estuary's real-time, no code model. It's magic that we're getting real time data without much effort and we don't have to spend time thinking about broken pipelines. We've also experienced fantastic support by Estuary.
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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this Zuora to Google Bigquery integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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