Two-way sync
Changes in DuckDB or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Keep DuckDB and PostgreSQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 PostgreSQL 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.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
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 | PostgreSQL objects | |
|---|---|---|
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. | |
| Views SQL views used to shape or filter data for downstream consumers. | Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Views Read-side projections used to expose joined or filtered data to a sync. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Materialized Views Precomputed result sets synced outward on a refresh schedule. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–PostgreSQL connection.
Changes in DuckDB or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever DuckDB or PostgreSQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single DuckDB or PostgreSQL record.
Track your DuckDB ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between DuckDB and PostgreSQL.
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.
Authenticate DuckDB and PostgreSQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the DuckDB and PostgreSQL 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and PostgreSQL: authenticate both systems, choose the objects to sync (such as DuckDB's Database files and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the DuckDB side: Schemas, Tables, Views, External files (Parquet/CSV/JSON), plus custom fields where DuckDB exposes them. On the PostgreSQL side: Primary and Unique Keys, JSONB Columns, Sequences, Custom Types and Enums. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for DuckDB and PostgreSQL: Migration with zero-downtime cutover; Shared reference data between services; Regional or environment copies. When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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). PostgreSQL: SQL wire protocol (PostgreSQL frontend/backend protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user. Stacksync manages authentication, retries, and rate limits on both sides.
DuckDB: DuckDB runs in-process like SQLite; there is no server, so integrations embed the engine or operate on the single-file databases it produces. PostgreSQL: Logical decoding of the write-ahead log (wal_level=logical) provides row-level change capture without adding triggers to user tables. Stacksync's field mapping accounts for these differences between DuckDB and PostgreSQL without custom code.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for DuckDB and PostgreSQL.