Real-time
Two-way sync
Changes in Dremio or DuckDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Dremio to DuckDB integration — real-time, two-way sync
Keep Dremio 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.
- 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Dremio and DuckDB
Connect DuckDB and Dremio 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 Dremio, 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 Dremio in real time, and result tables in Dremio sync back into DuckDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
- Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
- 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 Dremio 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 Dremio and keep DuckDB focused on its operational workload.
What you can sync between Dremio 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.
| Dremio objects | DuckDB objects | |
|---|---|---|
| Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | Attached databases Additional database files or external systems attached into one session for cross-source queries. | |
| Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | |
| Spaces and folders Namespaces that organize virtual datasets and govern access. | Schemas Namespaces within a database used to organize tables in sync outputs. | |
| Reflections Materialized accelerations that make repeated extraction queries cheaper. | Tables Columnar tables created via SQL; the destination for materialized sync data. | |
| Jobs Query execution records useful for monitoring sync workloads. | Views SQL views used to shape or filter data for downstream consumers. | |
| Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. |
What ships with Dremio ⇄ DuckDB
Connect Dremio and DuckDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–DuckDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dremio 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 Dremio or DuckDB record.
Observability
Monitoring
Track your Dremio ⇄ DuckDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Dremio and DuckDB.
How the Dremio and DuckDB connectors work
Dremio
- Integration surface
- Arrow Flight SQL, JDBC/ODBC, and a REST API
- Authentication
- Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
- Change detection
- Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Bounded by engine capacity and workload management rather than API rate limits
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 Dremio 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.
- 01
Connect your apps
Authenticate Dremio 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.
Dremio
connected
DuckDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dremio 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.
objects · Dremio ⇄ DuckDBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Dremio DuckDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dremio and DuckDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Dremio and DuckDB: authenticate both systems, choose the objects to sync (such as Dremio's Virtual datasets (views) and Apache Iceberg tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Dremio and DuckDB records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Dremio and DuckDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Dremio–DuckDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both Dremio and DuckDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Dremio: Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed. On DuckDB: Polling or full re-reads; no change feed or transaction log API. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Dremio side: Spaces and folders, Reflections, Jobs, Sources, plus custom fields where Dremio exposes them. On the DuckDB side: Schemas, Tables, Views, External files (Parquet/CSV/JSON). Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and DuckDB.
Popular · 8 of 386
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Dremio ⇄ Couchbase -
Dremio ⇄ Elasticsearch -
Dremio ⇄ Google Cloud Spanner - Dremio ⇄ Google Cloud SQL
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DuckDB ⇄ MotherDuck -
DuckDB ⇄ Databricks -
DuckDB ⇄ AWS S3 -
DuckDB ⇄ Actian Vector
No integrations match .
