Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or Google AlloyDB instantly reflect in both systems. No stale data, no manual imports.
Database
AWS Aurora PostgreSQL to Google AlloyDB integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL and Google AlloyDB 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
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect AWS Aurora PostgreSQL and Google AlloyDB
Keep AWS Aurora PostgreSQL and Google AlloyDB 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 AWS Aurora PostgreSQL and Google AlloyDB 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 a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
- 02 Feed operational dashboards from a read replica while the writer handles sync traffic.
- 03 Use logical replication to feed AlloyDB changes into warehouses or event pipelines without batch jobs.
- 04 Consolidate SaaS data into AlloyDB and serve analytics from its columnar engine without a separate OLAP store.
Common sync patterns
Cross-engine sync
Keep the same dataset live in both AWS Aurora PostgreSQL and Google AlloyDB, 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.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
What you can sync between AWS Aurora PostgreSQL and Google AlloyDB
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 AlloyDB objects | How this pairing syncs | |
|---|---|---|---|
| Tables The core sync unit; rows are matched across systems by primary key. | Tables Primary read/write target for bi-directional sync with CRMs and other systems. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Sequences ID generation relevant when external systems insert rows. | Primary keys and constraints is specific to AWS Aurora PostgreSQL and Sequences to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Replication Slots Logical replication artifacts that back log-based change capture. | Views and materialized views is specific to AWS Aurora PostgreSQL and Replication Slots to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Databases Standard PostgreSQL databases within an AlloyDB cluster that syncs connect to. | Foreign keys is specific to AWS Aurora PostgreSQL and Databases to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Schemas Namespaces used to separate synced SaaS data from application tables. | Replication slots and publications is specific to AWS Aurora PostgreSQL and Schemas to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Views Curated projections used as read-only sync sources. | Databases and schemas is specific to AWS Aurora PostgreSQL and Views to Google AlloyDB — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora PostgreSQL and Google AlloyDB
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.
AWS Aurora PostgreSQL Google AlloyDB Sub-second propagation
DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.
DeliveryEach detected change is applied to Google AlloyDB as a row-level write, with types converted between the two schemas.
Google AlloyDB AWS Aurora PostgreSQL Sub-second propagation
DetectionChanges in Google AlloyDB are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Google AlloyDB: No API-style rate limits; throughput is bounded by instance size.
What ships with AWS Aurora PostgreSQL ⇄ Google AlloyDB
Connect AWS Aurora PostgreSQL and Google AlloyDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Google AlloyDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL or Google AlloyDB 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 AWS Aurora PostgreSQL or Google AlloyDB record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ Google AlloyDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Google AlloyDB.
How the AWS Aurora PostgreSQL and Google AlloyDB connectors work
AWS Aurora PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
- Capabilities
- read · write · CDC
Google AlloyDB
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), with connectivity through the AlloyDB Auth Proxy or private IP
- Authentication
- Database credentials or IAM database authentication
- Change detection
- Log-based CDC via PostgreSQL logical replication; polling on timestamp columns as a fallback
- Capabilities
- read · write · CDC
- Rate limits
- No API-style rate limits; throughput is bounded by instance size
How it works
How to connect AWS Aurora PostgreSQL to Google AlloyDB — 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 AWS Aurora PostgreSQL and Google AlloyDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
AWS Aurora PostgreSQL
connected
Google AlloyDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL and Google AlloyDB 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 · AWS Aurora PostgreSQL ⇄ Google AlloyDBCustomers 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.
AWS Aurora PostgreSQL Google AlloyDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and Google AlloyDB integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Google AlloyDB: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Tables and Primary keys and constraints), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora PostgreSQL and Google AlloyDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–Google AlloyDB integration in-house.
-
Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Google AlloyDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. On Google AlloyDB: Log-based CDC via PostgreSQL logical replication; polling on timestamp columns as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the AWS Aurora PostgreSQL side: Foreign keys, Replication slots and publications, Databases and schemas, Tables, plus custom fields where AWS Aurora PostgreSQL exposes them. On the Google AlloyDB side: Databases, Schemas, Tables, Views. Stacksync auto-detects both schemas and converts types between the two systems.
-
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.
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
Every pair below is a real-time, two-way sync. Search all 393 integrations available for AWS Aurora PostgreSQL and Google AlloyDB.
Popular · 2 of 393
No integrations match .
