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Data warehouse ⇄ Business productivity

BigQuery to Monday integration — real-time, two-way sync

Keep BigQuery and Monday 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect BigQuery and Monday

Get the data locked inside Monday into BigQuery as live tables, and send results back where Monday can use them, without writing a pipeline.

Whatever Monday is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.

Stacksync syncs Subitems, Column values, Groups, Updates from Monday into tables in BigQuery continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in BigQuery can also be written back into fields in Monday where the tool can use them.

Common use cases

  • 01 Write closed deals or provisioning records from a CRM or ERP into monday.com Items to kick off delivery and onboarding boards.
  • 02 Mirror monday.com Boards, Groups, and Subitems into a warehouse for cross-project reporting on status and timelines without CSV exports.
  • 03 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • 04 Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools

Common sync patterns

Analytics on Monday's data

Records and events from Monday land in BigQuery as queryable tables, current within seconds and ready to join with the rest of the warehouse.

Cross-tool reporting

Combine Monday's data with data from every other synced system to answer questions no single tool can.

Where Monday accepts updates: operational write-back

Segments, scores, or reference values computed in BigQuery sync back onto records in Monday, putting analysis where the work happens.

What you can sync between BigQuery and Monday

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 Monday objects How this pairing syncs
Tables The syncable unit: only tables can be synced per the Stacksync docs. Column values Typed fields (status, date, people, numbers, connect-boards); polymorphic JSON usually written together via change_multiple_column_values. Tables is specific to BigQuery and Column values to Monday — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target fields. Groups Named sections that group items inside a board; synced as a grouping attribute or category field on the row. Partitioned tables is specific to BigQuery and Groups to Monday — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. Updates Comment and activity threads attached to items; read out into a database for reporting or written back as notes. Clustered tables is specific to BigQuery and Updates to Monday — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. Users Account members referenced by people columns; read to resolve owner and assignee IDs to names and emails. Datasets is specific to BigQuery and Users to Monday — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. Workspaces Top-level containers that hold boards; used to scope which boards a given sync covers. Projects is specific to BigQuery and Workspaces to Monday — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Monday

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

BigQuery Monday Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

DeliveryEach detected change is written to Monday through its API, with automatic retries and rate-limit backoff.

Monday BigQuery Sub-second propagation

DetectionMonday notifies Stacksync of record changes through webhook events. Board-scoped webhooks (create_item, change_column_value, item_deleted, and similar) for real-time events.

DeliveryEach detected change is applied to BigQuery as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • BigQuery: 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.
  • Monday: Complexity-budget limits: a single query caps at 5M complexity points and ~10M points/min per user token (1M on trial/free) over a sliding 60s window.
What ships with BigQuery ⇄ Monday

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Monday 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 Monday record.

Observability

Monitoring

Track your BigQuery ⇄ Monday 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 Monday.

How the BigQuery and Monday 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
BigQuery setup guide

Monday

Integration surface
GraphQL API (single endpoint, api.monday.com/v2)
Authentication
OAuth 2.0 for installed apps, or a per-user personal API token (admin/member scope); a date-based API version is sent via request header
Change detection
Board-scoped webhooks (create_item, change_column_value, item_deleted, and similar) for real-time events; polling falls back to the item updated_at field
Capabilities
read · write · webhooks
Rate limits
Complexity-budget limits: a single query caps at 5M complexity points and ~10M points/min per user token (1M on trial/free) over a sliding 60s window
Monday setup guide
How it works

How to connect BigQuery to Monday — 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 BigQuery and Monday 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
    BigQuery connected
    Monday connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the BigQuery and Monday 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 · BigQuery ⇄ Monday
    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
    BigQuery Monday
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery and Monday integration FAQ

SECURITY

Security teams trust 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
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ISO 27001
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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 547 integrations available for BigQuery and Monday.

Popular · 8 of 547
All BigQuery integrations All Monday integrations Browse all integrations
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