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Database ⇄ Data warehouse

DuckDB to Materialize integration — real-time, two-way sync

Keep DuckDB and Materialize 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 DuckDB and Materialize

Connect DuckDB and Materialize 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 Materialize, 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 Materialize in real time, and result tables in Materialize sync back into DuckDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • Read computed view results back into a CRM or application database as derived fields.
  • Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
  • Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
  • Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.

Serve warehouse results at database speed

Aggregates or model outputs computed in Materialize sync into DuckDB, 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.

Offload heavy reads

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

What you can sync between DuckDB and Materialize

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.

DuckDB objects Materialize objects
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. Sinks Outbound connections that emit view changes to Kafka topics.
Attached databases Additional database files or external systems attached into one session for cross-source queries. Indexes In-memory arrangements that make view reads fast for serving workloads.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Clusters Compute pools that isolate ingestion, view maintenance, and serving.
Schemas Namespaces within a database used to organize tables in sync outputs. Connections & Secrets Stored credentials and endpoints used by sources and sinks.
Tables Columnar tables created via SQL; the destination for materialized sync data. Schemas & Databases Namespaces that organize objects a sync targets.
Views SQL views used to shape or filter data for downstream consumers. Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines.
What ships with DuckDB ⇄ Materialize

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB or Materialize 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 DuckDB or Materialize record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between DuckDB and Materialize.

How the DuckDB and Materialize connectors work

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

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

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

    Choose tables

    Pick the DuckDB and Materialize 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 · DuckDB ⇄ Materialize
    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
    DuckDB Materialize
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

DuckDB and Materialize 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 DuckDB and Materialize.

Popular · 8 of 386
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