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Database ⇄ Data warehouse

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

Keep DuckDB and StarRocks 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 StarRocks

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

Common use cases

  • Continuously apply upserts from operational databases into Primary Key tables to keep analytics current
  • Serve customer-facing analytics from SaaS data synced into one analytical store
  • 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.

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between DuckDB and StarRocks

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 StarRocks objects
Views SQL views used to shape or filter data for downstream consumers. Partitions Time or range partitions that scope loads and retention.
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. Columns Columnar storage with types mapped from source systems during sync.
Attached databases Additional database files or external systems attached into one session for cross-source queries. Databases Top-level namespaces addressed exactly as in MySQL clients.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior.
Schemas Namespaces within a database used to organize tables in sync outputs. Materialized views Automatically maintained rollups used to accelerate queries on synced data.
Tables Columnar tables created via SQL; the destination for materialized sync data. Views Logical views for shaping analytical reads.
What ships with DuckDB ⇄ StarRocks

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB or StarRocks 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 StarRocks record.

Observability

Monitoring

Track your DuckDB ⇄ StarRocks 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 StarRocks.

How the DuckDB and StarRocks 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

StarRocks

Integration surface
MySQL wire protocol for SQL; HTTP-based Stream Load API for ingestion
Authentication
Database credentials (MySQL-compatible username/password)
Change detection
Query-based polling when reading; StarRocks is most often the destination side of a sync
Capabilities
read · write
Rate limits
Ingestion throughput is bounded by cluster resources rather than API quotas
How it works

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

    Choose tables

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

DuckDB and StarRocks 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 StarRocks.

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