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Data warehouse

Apache Druid to MotherDuck integration — real-time, two-way sync

Keep Apache Druid 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.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

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

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Why teams connect Apache Druid and MotherDuck

Keep tables consistent across Apache Druid and MotherDuck, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.

Stacksync syncs tables between Apache Druid and MotherDuck continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.

Common use cases

  • Feed operational records into Druid via batch ingestion so analysts get interactive slice-and-dice on fresh data.
  • Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
  • Land CRM and operational database records in MotherDuck so a small team gets warehouse-style analytics without cluster management
  • Sync modeled MotherDuck tables outward to operational tools for activation

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

What you can sync between Apache Druid and MotherDuck

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.

Apache Druid objects MotherDuck objects
Tasks Batch ingestion and compaction jobs monitored during data loads. Schemas Namespaces within a database used to organize synced tables.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Tables The main landing target for synced records and source for analysis.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Views Modeled projections used as outbound sync sources.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Database Shares Read-only copies of a database shared with other users or teams.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Attached Local DuckDB Databases Local files attached alongside cloud databases for hybrid queries.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Databases Cloud-hosted DuckDB databases that scope a sync's reads and writes.
What ships with Apache Druid ⇄ MotherDuck

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or MotherDuck 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 Apache Druid or MotherDuck record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apache Druid and MotherDuck connectors work

Apache Druid

Integration surface
REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
Authentication
Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
Change detection
Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
Capabilities
read · write
Rate limits
No fixed API quotas; query concurrency is bounded by broker and historical node capacity

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
How it works

How to connect Apache Druid to MotherDuck — 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 Apache Druid 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.

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

    Choose tables

    Pick the Apache Druid 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Apache Druid ⇄ MotherDuck
    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
    Apache Druid MotherDuck
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Druid and MotherDuck 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 Apache Druid and MotherDuck.

Popular · 8 of 386
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