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Data warehouse ⇄ Database

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

Keep Apache Druid 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.

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Why teams connect Apache Druid and DuckDB

Connect DuckDB and Apache Druid 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 DuckDB's rows in Apache Druid, 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 DuckDB where the services that read from it get them at normal query latency.

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

Common use cases

  • Expose product telemetry stored in Druid to business tools without granting direct cluster access.
  • Query aggregated event metrics from Druid and sync them into CRM account fields for usage-based selling.
  • Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.
  • Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.

Fresh analytics without loading windows

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

Offload heavy reads

Point analytical queries at the synced copy in Apache Druid and keep DuckDB focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from DuckDB land in Apache Druid as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between Apache Druid and DuckDB

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 DuckDB objects
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Attached databases Additional database files or external systems attached into one session for cross-source queries.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Schemas Namespaces within a database used to organize tables in sync outputs.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Tables Columnar tables created via SQL; the destination for materialized sync data.
Lookups Key-value mappings joined at query time, refreshable from external systems. Views SQL views used to shape or filter data for downstream consumers.
What ships with Apache Druid ⇄ DuckDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or DuckDB 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 DuckDB record.

Observability

Monitoring

Track your Apache Druid ⇄ DuckDB 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 DuckDB.

How the Apache Druid and DuckDB 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

DuckDB

Integration surface
In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
Authentication
None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
Change detection
Polling or full re-reads; no change feed or transaction log API
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by local compute and I/O
How it works

How to connect Apache Druid to DuckDB — 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 DuckDB 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
    DuckDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Druid 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.

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

Apache Druid and DuckDB 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 DuckDB.

Popular · 8 of 386
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