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Amazon Aurora to MongoDB integration — real-time, two-way sync

Keep Amazon Aurora 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.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon Aurora and MongoDB

Keep Amazon Aurora and MongoDB 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 Amazon Aurora 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 Stream row-level changes from Aurora into a warehouse for near-real-time analytics without batch exports.
  • 02 Consolidate several Aurora clusters into one reporting database.
  • 03 Keep a MongoDB-backed product catalog aligned with an ERP's item master in both directions.
  • 04 Consolidate documents from multiple clusters or tenants into a single warehouse-facing store.

Common sync patterns

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.

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

What you can sync between Amazon Aurora 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.

Amazon Aurora objects MongoDB objects How this pairing syncs
Databases Logical databases within a cluster that scope a sync connection. Databases Logical groupings of collections that scope a sync connection. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-only query-backed sources for downstream syncs. Views Read-only aggregation-defined sources for filtered sync datasets. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. GridFS files Chunked file storage whose metadata can be referenced by synced documents. Primary and Foreign Keys is specific to Amazon Aurora and GridFS files to MongoDB — each maps to any object or custom field on the other side.
Read Replicas Reader endpoints that syncs can target to keep load off the writer. Collections The table-like sync unit; each collection maps to a table or object in the paired system. Read Replicas is specific to Amazon Aurora and Collections to MongoDB — each maps to any object or custom field on the other side.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Documents BSON records created, updated, and deleted during syncs, keyed by _id. Schemas is specific to Amazon Aurora and Documents to MongoDB — each maps to any object or custom field on the other side.
Tables Relational tables synced bi-directionally at row level. Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. Tables is specific to Amazon Aurora and Embedded documents and arrays to MongoDB — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora 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.

Amazon Aurora MongoDB Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

DeliveryEach detected change is applied to MongoDB as a row-level write, with types converted between the two schemas.

MongoDB Amazon Aurora 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 Amazon Aurora as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
What ships with Amazon Aurora ⇄ MongoDB

Connect Amazon Aurora and MongoDB for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Aurora–MongoDB connection.

Real-time

Two-way sync

Changes in Amazon Aurora or MongoDB instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora 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 Amazon Aurora or MongoDB record.

Observability

Monitoring

Track your Amazon Aurora ⇄ MongoDB sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Aurora and MongoDB.

How the Amazon Aurora and MongoDB connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

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
MongoDB setup guide
How it works

How to connect Amazon Aurora 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.

  1. 01

    Connect your apps

    Authenticate Amazon Aurora 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon Aurora connected
    MongoDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon Aurora 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon Aurora ⇄ MongoDB
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon Aurora MongoDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Aurora and MongoDB integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 392 integrations available for Amazon Aurora and MongoDB.

Popular · 8 of 392
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