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Google Cloud SQL to IBM Informix integration — real-time, two-way sync

Keep Google Cloud SQL and IBM Informix 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 Google Cloud SQL and IBM Informix

Keep Google Cloud SQL and IBM Informix 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 Google Cloud SQL and IBM Informix 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 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 02 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
  • 03 Keep embedded or edge Informix instances aligned with a central operational database.
  • 04 Feed inventory and transaction data from legacy Informix applications into modern ERPs during migration.

Common sync patterns

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.

Cross-engine sync

Keep the same dataset live in both Google Cloud SQL and IBM Informix, so each workload runs on the engine that suits it.

What you can sync between Google Cloud SQL and IBM Informix

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.

Google Cloud SQL objects IBM Informix objects How this pairing syncs
Databases Scope the tables included in a sync configuration. Databases Top-level containers that scope a sync connection. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables Mapped directly to sync targets; schema changes can be propagated. Tables Relational tables mapped directly to sync targets. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Rows Read and written by primary key during each sync cycle. Rows The unit of read and write, keyed by primary key. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-only sources for shaping data before syncing it out. Views Read-only projections used to shape outbound data. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespace tables in PostgreSQL and SQL Server instances. TimeSeries objects Informix's native time-series type, usually exposed to syncs through virtual tables. Schemas is specific to Google Cloud SQL and TimeSeries objects to IBM Informix — each maps to any object or custom field on the other side.
Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Stored procedures Server-side logic sometimes invoked as part of write paths. Transaction logs is specific to Google Cloud SQL and Stored procedures to IBM Informix — each maps to any object or custom field on the other side.

How changes propagate between Google Cloud SQL and IBM Informix

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.

Google Cloud SQL IBM Informix 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 IBM Informix as a row-level write, with types converted between the two schemas.

IBM Informix Google Cloud SQL Sub-second propagation

DetectionChanges in IBM Informix are captured at the source via change data capture — no polling loop against its API. Informix's Change Data Capture API reading committed changes from logical logs.

DeliveryEach detected change is applied to Google Cloud SQL 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.
  • IBM Informix: Bounded by server resources and session limits rather than an API quota.
What ships with Google Cloud SQL ⇄ IBM Informix

Connect Google Cloud SQL and IBM Informix for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud SQL–IBM Informix connection.

Real-time

Two-way sync

Changes in Google Cloud SQL or IBM Informix instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Google Cloud SQL or IBM Informix 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 Google Cloud SQL or IBM Informix record.

Observability

Monitoring

Track your Google Cloud SQL ⇄ IBM Informix sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Google Cloud SQL and IBM Informix.

How the Google Cloud SQL and IBM Informix connectors work

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.

IBM Informix

Integration surface
SQL over JDBC/ODBC drivers; DRDA connectivity is also supported
Authentication
Database credentials
Change detection
Informix's Change Data Capture API reading committed changes from logical logs; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Bounded by server resources and session limits rather than an API quota.
How it works

How to connect Google Cloud SQL to IBM Informix — 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 Google Cloud SQL and IBM Informix 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
    Google Cloud SQL connected
    IBM Informix connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Google Cloud SQL and IBM Informix 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 · Google Cloud SQL ⇄ IBM Informix
    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
    Google Cloud SQL IBM Informix
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Google Cloud SQL and IBM Informix 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
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 392 integrations available for Google Cloud SQL and IBM Informix.

Popular · 8 of 392
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