Two-way sync
Changes in AWS Aurora PostgreSQL or DuckDB instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora PostgreSQL and DuckDB 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 DuckDB 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 DuckDB, 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 | DuckDB objects | |
|---|---|---|
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Schemas Namespaces within a database used to organize tables in sync outputs. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Tables Columnar tables created via SQL; the destination for materialized sync data. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Views SQL views used to shape or filter data for downstream consumers. | |
| Tables The core sync unit; rows are matched across systems by primary key. | External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Attached databases Additional database files or external systems attached into one session for cross-source queries. | |
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–DuckDB connection.
Changes in AWS Aurora PostgreSQL or DuckDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora PostgreSQL or DuckDB 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 DuckDB record.
Track your AWS Aurora PostgreSQL ⇄ DuckDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and DuckDB.
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 DuckDB 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 DuckDB 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 DuckDB: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Foreign keys and Replication slots and publications), 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 DuckDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–DuckDB integration in-house.
Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and DuckDB. 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 DuckDB: Polling or full re-reads; no change feed or transaction log API. 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: Rows, Columns, Primary keys and constraints, Views and materialized views, plus custom fields where AWS Aurora PostgreSQL exposes them. On the DuckDB side: Tables, Views, External files (Parquet/CSV/JSON), Attached databases. 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.
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 DuckDB.