Two-way sync
Changes in AWS Aurora PostgreSQL or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora PostgreSQL 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.
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 AWS Aurora PostgreSQL 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.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Keep the same dataset live in both AWS Aurora PostgreSQL and Google Cloud SQL, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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.
| AWS Aurora PostgreSQL objects | Google Cloud SQL objects | |
|---|---|---|
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Databases Scope the tables included in a sync configuration. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Schemas Namespace tables in PostgreSQL and SQL Server instances. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Tables Mapped directly to sync targets; schema changes can be propagated. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Rows Read and written by primary key during each sync cycle. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Views Read-only sources for shaping data before syncing it out. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Google Cloud SQL connection.
Changes in AWS Aurora PostgreSQL or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora PostgreSQL or Google Cloud SQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single AWS Aurora PostgreSQL or Google Cloud SQL record.
Track your AWS Aurora PostgreSQL ⇄ Google Cloud SQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Google Cloud SQL.
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.
Authenticate AWS Aurora PostgreSQL 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.
Pick the AWS Aurora PostgreSQL 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Google Cloud SQL: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Views and materialized views and Foreign keys), map fields visually, and changes propagate both ways in milliseconds — no code required.
AWS Aurora PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. 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.
AWS Aurora PostgreSQL: Replication slots retain WAL for their consumers, so an interrupted CDC sync can resume without losing changes. Google Cloud SQL: Connections use standard wire protocols, so existing drivers and ORMs work without modification. Stacksync's field mapping accounts for these differences between AWS Aurora PostgreSQL and Google Cloud SQL without custom code.
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 AWS Aurora PostgreSQL and Google Cloud SQL records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora PostgreSQL and Google Cloud SQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–Google Cloud SQL integration in-house.
Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Google Cloud SQL. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS Aurora PostgreSQL and Google Cloud SQL.