Real-time
Two-way sync
Changes in Citus or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Database
Citus to Google Cloud SQL integration — real-time, two-way sync
Keep Citus 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
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Migrated from MuleSoft
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Citus and Google Cloud SQL
Keep Citus 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 Citus 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 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
- 02 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.
- 03 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
- 04 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
Common sync patterns
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.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
What you can sync between Citus 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.
| Citus objects | Google Cloud SQL objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | 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. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | 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. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. | Local tables is specific to Citus and Transaction logs to Google Cloud SQL — each maps to any object or custom field on the other side. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. | Sequences is specific to Citus and Instances to Google Cloud SQL — each maps to any object or custom field on the other side. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Databases Scope the tables included in a sync configuration. | Distributed tables is specific to Citus and Databases to Google Cloud SQL — each maps to any object or custom field on the other side. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Tables Mapped directly to sync targets; schema changes can be propagated. | Reference tables is specific to Citus and Tables to Google Cloud SQL — each maps to any object or custom field on the other side. |
How changes propagate between Citus 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.
Citus Google Cloud SQL Sub-second propagation
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is applied to Google Cloud SQL as a row-level write, with types converted between the two schemas.
Google Cloud SQL Citus 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 Citus as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with Citus ⇄ Google Cloud SQL
Connect Citus and Google Cloud SQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Google Cloud SQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus 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 Citus or Google Cloud SQL record.
Observability
Monitoring
Track your Citus ⇄ 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 Citus and Google Cloud SQL.
How the Citus and Google Cloud SQL connectors work
Citus
- Integration surface
- PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
- Authentication
- Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
- Change detection
- PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
- Capabilities
- read · write · CDC
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 Citus 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 Citus 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.
Citus
connected
Google Cloud SQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus 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 · Citus ⇄ 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.
Citus Google Cloud SQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Google Cloud SQL integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Citus and Google Cloud SQL: authenticate both systems, choose the objects to sync (such as Citus's Schemas and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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.
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Common patterns for Citus and Google Cloud SQL: Migration with zero-downtime cutover; Shared reference data between services; Regional or environment copies. When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
-
Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). Google Cloud SQL: 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. Stacksync manages authentication, retries, and rate limits on both sides.
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Citus: Distributed tables are sharded by a declared distribution column, and reference tables are fully replicated to all nodes; the table type changes how writes and joins behave. Google Cloud SQL: The Cloud SQL Auth Proxy and language connectors provide IAM-authorized, encrypted connections without allowlisting IPs. Stacksync's field mapping accounts for these differences between Citus and Google Cloud SQL without custom code.
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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 Citus and Google Cloud SQL records are not retained after a sync operation.
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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