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Data warehouse ⇄ Database

MotherDuck to TimescaleDB integration — real-time, two-way sync

Keep MotherDuck and TimescaleDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect MotherDuck and TimescaleDB

Connect TimescaleDB and MotherDuck with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want TimescaleDB'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 TimescaleDB where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in TimescaleDB sync into MotherDuck in real time, and result tables in MotherDuck sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • Share curated, synced datasets with other teams through read-only database shares
  • Land CRM and operational database records in MotherDuck so a small team gets warehouse-style analytics without cluster management
  • Replicate subscription and billing events from operational Postgres tables into Timescale hypertables for time-series analysis.
  • Keep device or asset reference tables bi-directionally in sync between TimescaleDB and an ERP.

Operational data in the warehouse, minus the pipeline

Rows from TimescaleDB land in MotherDuck as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in MotherDuck sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between MotherDuck and TimescaleDB

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.

MotherDuck objects TimescaleDB objects
Databases Cloud-hosted DuckDB databases that scope a sync's reads and writes. Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs.
Schemas Namespaces within a database used to organize synced tables. Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly.
Tables The main landing target for synced records and source for analysis. Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems.
Views Modeled projections used as outbound sync sources. Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data.
Database Shares Read-only copies of a database shared with other users or teams. Views Standard SQL views used to shape or filter data for consumers.
Attached Local DuckDB Databases Local files attached alongside cloud databases for hybrid queries. Schemas Postgres namespaces used to separate synced datasets by team or environment.
What ships with MotherDuck ⇄ TimescaleDB

Connect MotherDuck and TimescaleDB for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every MotherDuck–TimescaleDB connection.

Real-time

Two-way sync

Changes in MotherDuck or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever MotherDuck or TimescaleDB 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 MotherDuck or TimescaleDB record.

Observability

Monitoring

Track your MotherDuck ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between MotherDuck and TimescaleDB.

How the MotherDuck and TimescaleDB connectors work

MotherDuck

Integration surface
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
Change detection
Polling; no log-based CDC or webhook surface is exposed
Capabilities
read · write
Rate limits
Subject to the platform's compute and concurrency limits rather than per-request API rate limits
MotherDuck setup guide

TimescaleDB

Integration surface
SQL wire protocol (PostgreSQL)
Authentication
Database credentials
Change detection
Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by database resources and connection limits.
How it works

How to connect MotherDuck to TimescaleDB — 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.

  1. 01

    Connect your apps

    Authenticate MotherDuck and TimescaleDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    MotherDuck connected
    TimescaleDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the MotherDuck and TimescaleDB 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · MotherDuck ⇄ TimescaleDB
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    MotherDuck TimescaleDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

MotherDuck and TimescaleDB integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for MotherDuck and TimescaleDB.

Popular · 8 of 386
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