Real-time
Two-way sync
Changes in DuckDB or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Database
DuckDB to TimescaleDB integration — real-time, two-way sync
Keep DuckDB and TimescaleDB 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 DuckDB and TimescaleDB
Keep DuckDB and TimescaleDB synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between DuckDB and TimescaleDB continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 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.
- Consolidate metrics from several services into one hypertable to serve a single reporting layer.
- Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both DuckDB and TimescaleDB, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
What you can sync between DuckDB and TimescaleDB
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 | TimescaleDB objects | |
|---|---|---|
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Views Standard SQL views used to shape or filter data for consumers. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Views SQL views used to shape or filter data for downstream consumers. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. |
What ships with DuckDB ⇄ TimescaleDB
Connect DuckDB and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DuckDB or TimescaleDB 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 TimescaleDB record.
Observability
Monitoring
Track your DuckDB ⇄ TimescaleDB 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 TimescaleDB.
How the DuckDB and TimescaleDB 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
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect DuckDB to TimescaleDB — 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 DuckDB and TimescaleDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DuckDB
connected
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DuckDB and TimescaleDB 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 · DuckDB ⇄ TimescaleDBCustomers 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.
DuckDB TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DuckDB and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and TimescaleDB: authenticate both systems, choose the objects to sync (such as DuckDB's Attached databases and Database files), map fields visually, and changes propagate both ways in milliseconds — no code required.
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DuckDB: 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). TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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DuckDB: It queries Parquet, CSV, and JSON files directly without importing them, which makes file-based exchange a natural sync pattern. TimescaleDB: Continuous aggregates materialize rollups incrementally instead of recomputing them on every query. Stacksync's field mapping accounts for these differences between DuckDB and TimescaleDB without custom code.
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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 DuckDB and TimescaleDB 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 DuckDB and TimescaleDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom DuckDB–TimescaleDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both DuckDB and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 DuckDB and TimescaleDB.
Popular · 8 of 386
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DuckDB ⇄ Redis Enterprise -
DuckDB ⇄ SAP ASE (Sybase) -
DuckDB ⇄ Scaleway Postgres -
DuckDB ⇄ TiDB -
TimescaleDB ⇄ Azure Cosmos DB -
TimescaleDB ⇄ Azure SQL Database -
TimescaleDB ⇄ Citus -
TimescaleDB ⇄ Couchbase
No integrations match .
