Real-time
Two-way sync
Changes in BigQuery or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Data warehouse
BigQuery to StarRocks integration — real-time, two-way sync
Keep BigQuery and StarRocks in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect BigQuery and StarRocks
Keep tables consistent across BigQuery and StarRocks, for a migration, a multi-warehouse stack, or a dataset two platforms both need.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between BigQuery and StarRocks continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
Common use cases
- Feed ML feature tables in BigQuery from operational systems on a continuous schedule
- Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
- Continuously apply upserts from operational databases into Primary Key tables to keep analytics current
- Serve customer-facing analytics from SaaS data synced into one analytical store
Serve tools that only connect to one platform
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Shared datasets across teams
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
Consolidation after M&A
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
What you can sync between BigQuery and StarRocks
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| BigQuery objects | StarRocks objects | |
|---|---|---|
| Datasets Organizational container — you pick which dataset’s tables to sync. | Partitions Time or range partitions that scope loads and retention. | |
| Projects Connection scope: the service account grants access per project. | Columns Columnar storage with types mapped from source systems during sync. | |
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Databases Top-level namespaces addressed exactly as in MySQL clients. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior. | |
| Clustered tables Supported; clustering is transparent to the sync. | Materialized views Automatically maintained rollups used to accelerate queries on synced data. |
What ships with BigQuery ⇄ StarRocks
Connect BigQuery and StarRocks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–StarRocks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever BigQuery or StarRocks data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single BigQuery or StarRocks record.
Observability
Monitoring
Track your BigQuery ⇄ StarRocks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between BigQuery and StarRocks.
How the BigQuery and StarRocks connectors work
BigQuery
- Integration surface
- GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
- Authentication
- Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
- Change detection
- Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
- Capabilities
- read · write · CDC
- Rate limits
- Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
StarRocks
- Integration surface
- MySQL wire protocol for SQL; HTTP-based Stream Load API for ingestion
- Authentication
- Database credentials (MySQL-compatible username/password)
- Change detection
- Query-based polling when reading; StarRocks is most often the destination side of a sync
- Capabilities
- read · write
- Rate limits
- Ingestion throughput is bounded by cluster resources rather than API quotas
How it works
How to connect BigQuery to StarRocks — three steps, no code
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
- 01
Connect your apps
Authenticate BigQuery and StarRocks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
BigQuery
connected
StarRocks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the BigQuery and StarRocks objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
objects · BigQuery ⇄ StarRocksCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
BigQuery StarRocksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
BigQuery and StarRocks integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between BigQuery and StarRocks: authenticate both systems, choose the objects to sync (such as BigQuery's Datasets and Projects), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed BigQuery and StarRocks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom BigQuery–StarRocks integration in-house.
-
Yes — Stacksync ships production-grade connectors for both BigQuery and StarRocks. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on BigQuery: Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in. On StarRocks: Query-based polling when reading; StarRocks is most often the destination side of a sync. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the BigQuery side: Datasets, Projects, Tables, Partitioned tables, plus custom fields where BigQuery exposes them. On the StarRocks side: Partitions, Columns, Databases, Tables. Stacksync auto-detects both schemas and converts types between the two systems.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
SECURITY
Security teams love Stacksync
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for BigQuery and StarRocks.
Popular · 8 of 386
-
BigQuery ⇄ Databricks -
BigQuery ⇄ AWS S3 -
BigQuery ⇄ Actian Vector -
BigQuery ⇄ Amazon Redshift -
StarRocks ⇄ Materialize -
StarRocks ⇄ Rockset -
StarRocks ⇄ Starburst Enterprise -
StarRocks ⇄ Teradata Vantage
No integrations match .
