Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Database
AWS Aurora PostgreSQL to Postgres Heroku integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and Postgres Heroku
Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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
- Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
- Capture row-level changes with logical replication and propagate them to SaaS tools without batch jobs.
- Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
- Keep several Heroku app databases aligned with one system of record
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 AWS Aurora PostgreSQL and Postgres Heroku, so each workload runs on the engine that suits it.
What you can sync between AWS Aurora PostgreSQL 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.
| AWS Aurora PostgreSQL objects | Postgres Heroku objects | |
|---|---|---|
| Replication slots and publications The logical replication objects that power log-based CDC. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Tables Standard Postgres tables; the primary two-way sync target for app data. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Views Read-side projections exposed to outbound syncs. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Materialized Views Precomputed result sets synced outward on refresh. | |
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. |
What ships with AWS Aurora PostgreSQL ⇄ Postgres Heroku
Connect AWS Aurora PostgreSQL and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL or Postgres Heroku record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ 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 AWS Aurora PostgreSQL and Postgres Heroku.
How the AWS Aurora PostgreSQL and Postgres Heroku 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
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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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.
AWS Aurora PostgreSQL
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL 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 · AWS Aurora PostgreSQL ⇄ 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.
AWS Aurora PostgreSQL Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and Postgres Heroku integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Postgres Heroku: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Replication slots and publications and Databases and schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the AWS Aurora PostgreSQL side: Replication slots and publications, Databases and schemas, Tables, Rows, plus custom fields where AWS Aurora PostgreSQL exposes them. On the Postgres Heroku side: Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases. Stacksync auto-detects both schemas and converts types between the two systems.
SECURITY
Security teams love 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
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS Aurora PostgreSQL and Postgres Heroku.
Popular · 8 of 386
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AWS Aurora PostgreSQL ⇄ IBM AS/400 -
AWS Aurora PostgreSQL ⇄ IBM Informix -
AWS Aurora PostgreSQL ⇄ InfluxDB -
AWS Aurora PostgreSQL ⇄ InterSystems IRIS -
Postgres Heroku ⇄ Scaleway Postgres -
Postgres Heroku ⇄ TiDB -
Postgres Heroku ⇄ TimescaleDB -
Postgres Heroku ⇄ VoltDB
No integrations match .
