Two-way sync
Changes in AWS Aurora PostgreSQL or MotherDuck instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora PostgreSQL and MotherDuck in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want AWS Aurora PostgreSQL's rows in MotherDuck, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in AWS Aurora PostgreSQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in AWS Aurora PostgreSQL sync into MotherDuck in real time, and result tables in MotherDuck sync back into AWS Aurora PostgreSQL, with schema and type mapping between the two systems handled for you.
Rows from AWS Aurora PostgreSQL land in MotherDuck as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in MotherDuck sync into AWS Aurora PostgreSQL, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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 | MotherDuck objects | |
|---|---|---|
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Databases Cloud-hosted DuckDB databases that scope a sync's reads and writes. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Schemas Namespaces within a database used to organize synced tables. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Tables The main landing target for synced records and source for analysis. | |
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Views Modeled projections used as outbound sync sources. | |
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Database Shares Read-only copies of a database shared with other users or teams. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Attached Local DuckDB Databases Local files attached alongside cloud databases for hybrid queries. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–MotherDuck connection.
Changes in AWS Aurora PostgreSQL or MotherDuck instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora PostgreSQL or MotherDuck 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 MotherDuck record.
Track your AWS Aurora PostgreSQL ⇄ MotherDuck sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and MotherDuck.
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 MotherDuck 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 MotherDuck 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 MotherDuck: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Databases and schemas and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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 MotherDuck: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from AWS Aurora PostgreSQL land in MotherDuck as they change, replacing hand-built CDC and batch extract jobs.
AWS Aurora PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. MotherDuck: SQL through DuckDB clients and drivers using a MotherDuck (md:) connection. Authentication: Access token created in MotherDuck (Settings > General > Create Token), pasted into Stacksync; database name and schema configurable if not using defaults. Stacksync manages authentication, retries, and rate limits on both sides.
MotherDuck: MotherDuck is built on DuckDB, so integrations use DuckDB SQL and connect through standard DuckDB client libraries with an md: connection string. AWS Aurora PostgreSQL: Replication slots retain WAL for their consumers, so an interrupted CDC sync can resume without losing changes. Stacksync's field mapping accounts for these differences between AWS Aurora PostgreSQL and MotherDuck without custom code.
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 MotherDuck records are not retained after a sync operation.
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 MotherDuck.