Real-time
Two-way sync
Changes in DuckDB or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Database
DuckDB to Google Cloud SQL integration — real-time, two-way sync
Keep DuckDB and Google Cloud SQL 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
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Migrated from Celigo
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Migrated from Matillion
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect DuckDB and Google Cloud SQL
Keep DuckDB and Google Cloud SQL synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between DuckDB and Google Cloud SQL continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
- 02 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
- 03 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
- 04 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
Common sync patterns
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both DuckDB and Google Cloud SQL, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
What you can sync between DuckDB and Google Cloud SQL
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.
| DuckDB objects | Google Cloud SQL objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Namespaces within a database used to organize tables in sync outputs. | Schemas Namespace tables in PostgreSQL and SQL Server instances. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Tables Mapped directly to sync targets; schema changes can be propagated. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views SQL views used to shape or filter data for downstream consumers. | Views Read-only sources for shaping data before syncing it out. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Rows Read and written by primary key during each sync cycle. | Database files is specific to DuckDB and Rows to Google Cloud SQL — each maps to any object or custom field on the other side. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. | External files (Parquet/CSV/JSON) is specific to DuckDB and Transaction logs to Google Cloud SQL — each maps to any object or custom field on the other side. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. | Attached databases is specific to DuckDB and Instances to Google Cloud SQL — each maps to any object or custom field on the other side. |
How changes propagate between DuckDB and Google Cloud SQL
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.
DuckDB Google Cloud SQL Interval-based propagation
DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.
DeliveryEach detected change is applied to Google Cloud SQL as a row-level write, with types converted between the two schemas.
Google Cloud SQL DuckDB Sub-second propagation
DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.
DeliveryEach detected change is applied to DuckDB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
- Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with DuckDB ⇄ Google Cloud SQL
Connect DuckDB and Google Cloud SQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–Google Cloud SQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DuckDB or Google Cloud SQL 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 DuckDB or Google Cloud SQL record.
Observability
Monitoring
Track your DuckDB ⇄ Google Cloud SQL sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between DuckDB and Google Cloud SQL.
How the DuckDB and Google Cloud SQL connectors work
DuckDB
- Integration surface
- In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
- Authentication
- None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
- Change detection
- Polling or full re-reads; no change feed or transaction log API
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by local compute and I/O
Google Cloud SQL
- Integration surface
- Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
- Authentication
- Database credentials; IAM database authentication is available for MySQL and PostgreSQL
- Change detection
- Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
- Capabilities
- read · write · CDC
- Rate limits
- Constrained by instance size and connection limits rather than API quotas.
How it works
How to connect DuckDB to Google Cloud SQL — 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 DuckDB and Google Cloud SQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DuckDB
connected
Google Cloud SQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DuckDB and Google Cloud SQL 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 · DuckDB ⇄ Google Cloud SQLCustomers 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.
DuckDB Google Cloud SQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DuckDB and Google Cloud SQL integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and Google Cloud SQL: authenticate both systems, choose the objects to sync (such as DuckDB's Schemas and Tables), 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 DuckDB and Google Cloud SQL 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 DuckDB and Google Cloud SQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom DuckDB–Google Cloud SQL integration in-house.
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Yes — Stacksync ships production-grade connectors for both DuckDB and Google Cloud SQL. 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 DuckDB: Polling or full re-reads; no change feed or transaction log API. On Google Cloud SQL: Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback. 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 DuckDB side: Attached databases, Database files, Schemas, Tables, plus custom fields where DuckDB exposes them. On the Google Cloud SQL side: Tables, Rows, Views, Transaction logs. Stacksync auto-detects both schemas and converts types between the two systems.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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
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