Two-way sync
Changes in DuckDB or MongoDB instantly reflect in both systems. No stale data, no manual imports.
Keep DuckDB and MongoDB 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 MongoDB 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.
Keep the same dataset live in both DuckDB and MongoDB, so each workload runs on the engine that suits it.
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.
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 | MongoDB objects | |
|---|---|---|
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Views Read-only aggregation-defined sources for filtered sync datasets. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Change streams The oplog-backed event feed that powers real-time change capture. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | GridFS files Chunked file storage whose metadata can be referenced by synced documents. | |
| Views SQL views used to shape or filter data for downstream consumers. | Databases Logical groupings of collections that scope a sync connection. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Collections The table-like sync unit; each collection maps to a table or object in the paired system. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Documents BSON records created, updated, and deleted during syncs, keyed by _id. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–MongoDB connection.
Changes in DuckDB or MongoDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever DuckDB or MongoDB 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 MongoDB record.
Track your DuckDB ⇄ MongoDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between DuckDB and MongoDB.
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 MongoDB 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 MongoDB 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 MongoDB: 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.
Change detection on DuckDB: Polling or full re-reads; no change feed or transaction log API. On MongoDB: MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the DuckDB side: Attached databases, Database files, Schemas, Tables, plus custom fields where DuckDB exposes them. On the MongoDB side: Databases, Collections, Documents, Embedded documents and arrays. 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 MongoDB: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both DuckDB and MongoDB, so each workload runs on the engine that suits it.
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). MongoDB: MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management. Authentication: Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required. Stacksync manages authentication, retries, and rate limits on both sides.
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 MongoDB.