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Data warehouse

Apache Doris to BigQuery integration — real-time, two-way sync

Keep Apache Doris and BigQuery in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Apache Doris and BigQuery

Keep tables consistent across Apache Doris and BigQuery, 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 Apache Doris and BigQuery 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

  • Continuously upsert changing records into Unique Key tables so analytics reflect current state rather than append-only history.
  • Read aggregates from Doris and sync them into business tools like CRMs or spreadsheets.
  • Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • Feed ML feature tables in BigQuery from operational systems on a continuous schedule

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

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.

What you can sync between Apache Doris and BigQuery

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.

Apache Doris objects BigQuery objects
Users and Roles Principals used to grant the sync connection scoped access. Partitioned tables Synced like regular tables; partition columns map to target fields.
Databases Logical containers that scope connections and grants. Clustered tables Supported; clustering is transparent to the sync.
Tables Columnar tables in one of Doris's table models, used as sync destinations. Datasets Organizational container — you pick which dataset’s tables to sync.
Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. Projects Connection scope: the service account grants access per project.
Aggregate Key Tables Tables that pre-aggregate on load, used for metric rollups. Tables The syncable unit: only tables can be synced per the Stacksync docs.
What ships with Apache Doris ⇄ BigQuery

Connect Apache Doris and BigQuery for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Doris–BigQuery connection.

Real-time

Two-way sync

Changes in Apache Doris or BigQuery instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Doris or BigQuery 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 Apache Doris or BigQuery record.

Observability

Monitoring

Track your Apache Doris ⇄ BigQuery sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Doris and BigQuery.

How the Apache Doris and BigQuery connectors work

Apache Doris

Integration surface
MySQL wire protocol for SQL access; HTTP APIs (such as Stream Load) for bulk ingestion
Authentication
Database credentials
Change detection
Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs
Capabilities
read · write
Rate limits
No API quotas; load throughput depends on cluster resources and load-job configuration

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
BigQuery setup guide
How it works

How to connect Apache Doris to BigQuery — 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.

  1. 01

    Connect your apps

    Authenticate Apache Doris and BigQuery with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Apache Doris connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Doris and BigQuery 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Apache Doris ⇄ BigQuery
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Apache Doris BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Doris and BigQuery integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Doris and BigQuery.

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