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Citus to Google Cloud Spanner integration — real-time, two-way sync

Keep Citus and Google Cloud Spanner 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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Why teams connect Citus and Google Cloud Spanner

Keep Citus and Google Cloud Spanner 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 Spanner 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 Consolidate per-tenant rows from distributed tables into per-customer reporting databases.
  • 02 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
  • 03 Push billing or entitlement changes from finance tools into Spanner tables the application reads at runtime.
  • 04 Use change streams to feed near-real-time copies of operational tables into an analytics warehouse.

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 Citus and Google Cloud Spanner, 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 Citus and Google Cloud Spanner

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 Spanner objects How this pairing syncs
Views Curated projections over distributed data, often used as read-only sync sources. Views Read-only projections useful for shaping data before it leaves Spanner. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Sequences Key generators that matter when external writes must not collide with application inserts. Rows The unit of read and write in each sync cycle, keyed by primary key. Sequences is specific to Citus and Rows to Google Cloud Spanner — 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. Interleaved tables Child rows physically co-located with parents; synced as related records. Distributed tables is specific to Citus and Interleaved tables to Google Cloud Spanner — 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. Secondary indexes Used to make incremental read queries efficient on non-key columns. Reference tables is specific to Citus and Secondary indexes to Google Cloud Spanner — each maps to any object or custom field on the other side.
Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. Change streams Capture inserts, updates, and deletes for log-style change data capture. Local tables is specific to Citus and Change streams to Google Cloud Spanner — each maps to any object or custom field on the other side.
Schemas Standard Postgres namespaces used to scope what a sync user can read and write. Databases Top-level containers that scope schema and sync configuration. Schemas is specific to Citus and Databases to Google Cloud Spanner — each maps to any object or custom field on the other side.

How changes propagate between Citus and Google Cloud Spanner

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 Spanner 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 Spanner as a row-level write, with types converted between the two schemas.

Google Cloud Spanner Citus Sub-second propagation

DetectionChanges in Google Cloud Spanner are captured at the source via change data capture — no polling loop against its API. Change streams (log-style CDC), or timestamp-based polling queries.

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

Rate-limit considerations

  • Google Cloud Spanner: Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.
What ships with Citus ⇄ Google Cloud Spanner

Connect Citus and Google Cloud Spanner for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Google Cloud Spanner connection.

Real-time

Two-way sync

Changes in Citus or Google Cloud Spanner instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Citus or Google Cloud Spanner 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 Spanner record.

Observability

Monitoring

Track your Citus ⇄ Google Cloud Spanner 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 Spanner.

How the Citus and Google Cloud Spanner 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 Spanner

Integration surface
gRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects)
Authentication
Google Cloud IAM (service accounts)
Change detection
Change streams (log-style CDC), or timestamp-based polling queries
Capabilities
read · write · CDC
Rate limits
Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.
How it works

How to connect Citus to Google Cloud Spanner — 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 Citus and Google Cloud Spanner 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
    Citus connected
    Google Cloud Spanner connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Citus and Google Cloud Spanner 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 · Citus ⇄ Google Cloud Spanner
    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
    Citus Google Cloud Spanner
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Citus and Google Cloud Spanner 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
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:

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 355 integrations available for Citus and Google Cloud Spanner.

Popular · 5 of 355
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