Two-way sync
Changes in AWS Aurora PostgreSQL or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora PostgreSQL and PostgreSQL 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 PostgreSQL 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.
Keep the same dataset live in both AWS Aurora PostgreSQL and PostgreSQL, 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.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
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 | PostgreSQL objects | |
|---|---|---|
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Columns Field-level mapping targets; types are mapped to the connected system's field types. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–PostgreSQL connection.
Changes in AWS Aurora PostgreSQL or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora PostgreSQL or PostgreSQL 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 PostgreSQL record.
Track your AWS Aurora PostgreSQL ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and PostgreSQL.
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 PostgreSQL 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 PostgreSQL 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 PostgreSQL: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Primary keys and constraints and Views and materialized views), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the AWS Aurora PostgreSQL side: Tables, Rows, Columns, Primary keys and constraints, plus custom fields where AWS Aurora PostgreSQL exposes them. On the PostgreSQL side: Sequences, Custom Types and Enums, 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.
Common patterns for AWS Aurora PostgreSQL and PostgreSQL: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both AWS Aurora PostgreSQL and PostgreSQL, so each workload runs on the engine that suits it.
AWS Aurora PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. PostgreSQL: SQL wire protocol (PostgreSQL frontend/backend protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user. 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. PostgreSQL: Renaming schemas, tables, or columns will break Stacksync configuration (requires manual sync configuration update). Stacksync's field mapping accounts for these differences between AWS Aurora PostgreSQL and PostgreSQL without custom code.
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 PostgreSQL.