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Database ⇄ Data warehouse

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

Keep DuckDB and Snowflake 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 Snowflake

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

Common use cases

  • Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL
  • Activate modeled Snowflake tables by syncing scores and attributes back into CRM fields sales can act on
  • 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 Snowflake and keep DuckDB focused on its operational workload.

Operational data in the warehouse, minus the pipeline

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

What you can sync between DuckDB and Snowflake

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 Snowflake objects
Schemas Namespaces within a database used to organize tables in sync outputs. Streams Row-level change records on a table, consumed to process deltas instead of full scans.
Tables Columnar tables created via SQL; the destination for materialized sync data. Stages File staging areas used for bulk loads into synced tables.
Views SQL views used to shape or filter data for downstream consumers. Tasks Scheduled SQL used to transform synced data after it lands.
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. VARIANT Columns Semi-structured JSON payloads stored alongside relational columns.
Attached databases Additional database files or external systems attached into one session for cross-source queries. Virtual Warehouses The compute a sync's queries run on, sized independently of storage.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Databases Top-level containers that scope which data a sync can touch.
What ships with DuckDB ⇄ Snowflake

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB or Snowflake 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 Snowflake record.

Observability

Monitoring

Track your DuckDB ⇄ Snowflake 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 Snowflake.

How the DuckDB and Snowflake 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

Snowflake

Integration surface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
Capabilities
read · write · CDC
Rate limits
No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
Snowflake setup guide
How it works

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

    Choose tables

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

DuckDB and Snowflake 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 Snowflake.

Popular · 8 of 386
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