Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or MongoDB instantly reflect in both systems. No stale data, no manual imports.
Database
AWS Aurora PostgreSQL to MongoDB integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL 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.
- 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 AWS Aurora PostgreSQL and MongoDB
Keep AWS Aurora PostgreSQL and MongoDB synchronized in real time, across engines, regions, or services, in one or both directions.
Teams connect AWS Aurora PostgreSQL and MongoDB when relational and document workloads must share the same data. MongoDB Collections and Documents sync into Aurora tables for SQL joins and reporting, while rows from Aurora appear as Documents for services built on MongoDB.
Stacksync syncs tables or collections between AWS Aurora PostgreSQL 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.
Common use cases
- 01 Run SQL analytics and joins on data that originates in MongoDB Collections.
- 02 Serve a MongoDB-based application from records mastered in Aurora PostgreSQL.
- 03 Flatten embedded documents and arrays into relational views for BI tools.
- 04 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
Common sync patterns
Documents to rows
MongoDB Documents, including embedded documents and arrays, sync into Aurora PostgreSQL tables with columns mapped for SQL access.
Relational to collections
Aurora rows replicate into MongoDB Collections so document-oriented services read current data.
Schema-aligned sync
Collections map to tables with primary keys and indexes maintained on both sides.
What you can sync between AWS Aurora PostgreSQL and MongoDB
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.
| AWS Aurora PostgreSQL objects | MongoDB objects | How this pairing syncs | |
|---|---|---|---|
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Collections The table-like sync unit; each collection maps to a table or object in the paired system. | Columns is specific to AWS Aurora PostgreSQL and Collections to MongoDB — each maps to any object or custom field on the other side. | |
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Documents BSON records created, updated, and deleted during syncs, keyed by _id. | Primary keys and constraints is specific to AWS Aurora PostgreSQL and Documents to MongoDB — each maps to any object or custom field on the other side. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. | Views and materialized views is specific to AWS Aurora PostgreSQL and Embedded documents and arrays to MongoDB — each maps to any object or custom field on the other side. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Indexes Keep lookups by sync key fast on large collections. | Foreign keys is specific to AWS Aurora PostgreSQL and Indexes to MongoDB — each maps to any object or custom field on the other side. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Views Read-only aggregation-defined sources for filtered sync datasets. | Replication slots and publications is specific to AWS Aurora PostgreSQL and Views to MongoDB — each maps to any object or custom field on the other side. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Change streams The oplog-backed event feed that powers real-time change capture. | Databases and schemas is specific to AWS Aurora PostgreSQL and Change streams to MongoDB — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora PostgreSQL and MongoDB
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
AWS Aurora PostgreSQL MongoDB Sub-second propagation
DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.
DeliveryEach detected change is applied to MongoDB as a row-level write, with types converted between the two schemas.
MongoDB AWS Aurora PostgreSQL Sub-second propagation
DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
What ships with AWS Aurora PostgreSQL ⇄ MongoDB
Connect AWS Aurora PostgreSQL and MongoDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–MongoDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL or MongoDB 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 AWS Aurora PostgreSQL or MongoDB record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ MongoDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and MongoDB.
How the AWS Aurora PostgreSQL and MongoDB connectors work
AWS Aurora PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
- Capabilities
- read · write · CDC
MongoDB
- Integration surface
- 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
- Change detection
- 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
- Capabilities
- read · write · CDC
How it works
How to connect AWS Aurora PostgreSQL to MongoDB — 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 AWS Aurora PostgreSQL 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.
AWS Aurora PostgreSQL
connected
MongoDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL 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.
objects · AWS Aurora PostgreSQL ⇄ MongoDBCustomers 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.
AWS Aurora PostgreSQL MongoDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and MongoDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and MongoDB: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Columns and Primary keys and constraints), map fields visually, and changes propagate both ways in milliseconds — no code required.
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AWS Aurora PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. 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.
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AWS Aurora PostgreSQL: Logical replication uses publications and replication slots, so CDC reads changes from the write-ahead log without polling production tables. MongoDB: Change streams expose ordered change events with resume tokens, so an interrupted sync can pick up exactly where it stopped without a full re-read. Stacksync's field mapping accounts for these differences between AWS Aurora PostgreSQL and MongoDB 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 AWS Aurora PostgreSQL and MongoDB 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 AWS Aurora PostgreSQL and MongoDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–MongoDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and MongoDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
SECURITY
Security teams trust 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
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 486 integrations available for AWS Aurora PostgreSQL and MongoDB.
Popular · 5 of 486
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AWS Aurora PostgreSQL ⇄ InfluxDB -
MongoDB ⇄ MarkLogic -
MongoDB ⇄ Neo4j -
MongoDB ⇄ OCI Database (Oracle Cloud) -
MongoDB ⇄ OpenSearch
No integrations match .
