Real-time
Two-way sync
Changes in BigQuery or MongoDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
BigQuery to MongoDB integration — real-time, two-way sync
Keep BigQuery and MongoDB 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
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Migrated from Celigo
Why teams connect BigQuery and MongoDB
Connect MongoDB and BigQuery with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want MongoDB's rows in BigQuery, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in MongoDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in MongoDB sync into BigQuery in real time, and result tables in BigQuery sync back into MongoDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
- Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
- Consolidate documents from multiple clusters or tenants into a single warehouse-facing store.
- Sync MongoDB collections with a CRM so customer documents written by the application appear as CRM records, and CRM edits flow back as document updates.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in BigQuery and keep MongoDB focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from MongoDB land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between BigQuery and MongoDB
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 | MongoDB objects | |
|---|---|---|
| Datasets Organizational container — you pick which dataset’s tables to sync. | Views Read-only aggregation-defined sources for filtered sync datasets. | |
| Projects Connection scope: the service account grants access per project. | Change streams The oplog-backed event feed that powers real-time change capture. | |
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | GridFS files Chunked file storage whose metadata can be referenced by synced documents. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Databases Logical groupings of collections that scope a sync connection. | |
| Clustered tables Supported; clustering is transparent to the sync. | Collections The table-like sync unit; each collection maps to a table or object in the paired system. |
What ships with BigQuery ⇄ MongoDB
Connect BigQuery and MongoDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–MongoDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever BigQuery or MongoDB 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 MongoDB record.
Observability
Monitoring
Track your BigQuery ⇄ MongoDB 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 MongoDB.
How the BigQuery and MongoDB 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
MongoDB
- Integration surface
- MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
- Authentication
- Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
- Change detection
- MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
- Capabilities
- read · write · CDC
How it works
How to connect BigQuery to MongoDB — 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 MongoDB 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
MongoDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the BigQuery and MongoDB 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 ⇄ MongoDBCustomers 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 MongoDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
BigQuery and MongoDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between BigQuery and MongoDB: 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.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means BigQuery and MongoDB records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed BigQuery and MongoDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom BigQuery–MongoDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both BigQuery and MongoDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 MongoDB: MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the BigQuery side: Partitioned tables, Clustered tables, Datasets, Projects, plus custom fields where BigQuery exposes them. On the MongoDB side: Indexes, Views, Change streams, GridFS files. Stacksync auto-detects both schemas and converts types between the two systems.
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 MongoDB.
Popular · 8 of 386
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BigQuery ⇄ IBM Informix -
BigQuery ⇄ InfluxDB -
BigQuery ⇄ InterSystems IRIS -
BigQuery ⇄ MarkLogic -
MongoDB ⇄ Apache Doris -
MongoDB ⇄ Apache Druid -
MongoDB ⇄ Apache Hive -
MongoDB ⇄ Apache Impala
No integrations match .
