Two-way sync
Changes in Citus or MotherDuck instantly reflect in both systems. No stale data, no manual imports.
Keep Citus 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 Citus'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 Citus where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Citus sync into MotherDuck in real time, and result tables in MotherDuck sync back into Citus, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in MotherDuck and keep Citus focused on its operational workload.
Rows from Citus land in MotherDuck as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in MotherDuck sync into Citus, where whatever reads from that database gets them without querying the warehouse.
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.
| Citus objects | MotherDuck objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Schemas Namespaces within a database used to organize synced tables. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | Views Modeled projections used as outbound sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Tables The main landing target for synced records and source for analysis. | Sequences is specific to Citus and Tables to MotherDuck — each maps to any object or custom field on the other side. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Database Shares Read-only copies of a database shared with other users or teams. | Distributed tables is specific to Citus and Database Shares to MotherDuck — each maps to any object or custom field on the other side. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Attached Local DuckDB Databases Local files attached alongside cloud databases for hybrid queries. | Reference tables is specific to Citus and Attached Local DuckDB Databases to MotherDuck — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Databases Cloud-hosted DuckDB databases that scope a sync's reads and writes. | Local tables is specific to Citus and Databases to MotherDuck — each maps to any object or custom field on the other side. |
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.
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is applied to MotherDuck as a row-level write, with types converted between the two schemas.
DetectionStacksync polls MotherDuck for changes on an incremental schedule, reading only records changed since the previous pass. Polling.
DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–MotherDuck connection.
Changes in Citus or MotherDuck instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Citus 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 Citus or MotherDuck record.
Track your Citus ⇄ MotherDuck sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Citus 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 Citus 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 Citus 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 Citus and MotherDuck: authenticate both systems, choose the objects to sync (such as Citus's Schemas and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. On MotherDuck: Polling; no log-based CDC or webhook surface is exposed. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the MotherDuck side: Tables, Views, Database Shares, Attached Local DuckDB Databases, plus custom fields where MotherDuck exposes them. On the Citus side: Views, Sequences, Distributed tables, Reference tables. 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 Citus and MotherDuck: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in MotherDuck and keep Citus focused on its operational workload.
Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). 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.
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 377 integrations available for Citus and MotherDuck.