Real-time
Two-way sync
Changes in Google Cloud Spanner or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Database
Google Cloud Spanner to Postgres Heroku integration — real-time, two-way sync
Keep Google Cloud Spanner and Postgres Heroku 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 Google Cloud Spanner and Postgres Heroku
Keep Google Cloud Spanner and Postgres Heroku 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 Spanner and Postgres Heroku 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 Use change streams to feed near-real-time copies of operational tables into an analytics warehouse.
- 02 Run a two-way sync between Spanner and a SaaS tool so edits made by ops teams land back in the application database.
- 03 Keep several Heroku app databases aligned with one system of record
- 04 Reflect billing and subscription records into the app database so product logic reads local rows
Common sync patterns
Cross-engine sync
Keep the same dataset live in both Google Cloud Spanner and Postgres Heroku, 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 Google Cloud Spanner and Postgres Heroku
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 Spanner objects | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Tables Relational tables mapped one-to-one to sync targets. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Read-only projections useful for shaping data before it leaves Spanner. | Views Read-side projections exposed to outbound syncs. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Rows The unit of read and write in each sync cycle, keyed by primary key. | Sequences Generate surrogate keys for rows created by inbound syncs. | Rows is specific to Google Cloud Spanner and Sequences to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Interleaved tables Child rows physically co-located with parents; synced as related records. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | Interleaved tables is specific to Google Cloud Spanner and Follower Databases to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Secondary indexes Used to make incremental read queries efficient on non-key columns. | Materialized Views Precomputed result sets synced outward on refresh. | Secondary indexes is specific to Google Cloud Spanner and Materialized Views to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Change streams Capture inserts, updates, and deletes for log-style change data capture. | Schemas Namespaces that scope which tables a sync reads and writes. | Change streams is specific to Google Cloud Spanner and Schemas to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between Google Cloud Spanner and Postgres Heroku
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 Spanner Postgres Heroku 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 Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku Google Cloud Spanner Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
DeliveryEach detected change is applied to Google Cloud Spanner 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.
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Google Cloud Spanner ⇄ Postgres Heroku
Connect Google Cloud Spanner and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud Spanner–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Google Cloud Spanner or Postgres Heroku 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 Spanner or Postgres Heroku record.
Observability
Monitoring
Track your Google Cloud Spanner ⇄ Postgres Heroku 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 Spanner and Postgres Heroku.
How the Google Cloud Spanner and Postgres Heroku connectors work
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.
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect Google Cloud Spanner to Postgres Heroku — 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 Google Cloud Spanner and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Google Cloud Spanner
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Google Cloud Spanner and Postgres Heroku 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 · Google Cloud Spanner ⇄ Postgres HerokuCustomers 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.
Google Cloud Spanner Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Google Cloud Spanner and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Google Cloud Spanner and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Google Cloud Spanner's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Google Cloud Spanner: GRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects). Authentication: Google Cloud IAM (service accounts). Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.
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Google Cloud Spanner: Change streams record row-level inserts, updates, and deletes and can be consumed through the API for CDC pipelines. Postgres Heroku: Credentials are managed by Heroku through the DATABASE_URL config var and can rotate, so integrations should tolerate credential changes. Stacksync's field mapping accounts for these differences between Google Cloud Spanner and Postgres Heroku 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 Google Cloud Spanner and Postgres Heroku records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Google Cloud Spanner and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Google Cloud Spanner–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both Google Cloud Spanner and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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