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Amazon Aurora to Azure Cosmos DB integration — real-time, two-way sync

Keep Amazon Aurora and Azure Cosmos DB 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 Azure Cosmos DB

Keep Amazon Aurora and Azure Cosmos DB 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 Azure Cosmos DB 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 Write enriched or scored records from analytics pipelines back into the Aurora tables that power an application.
  • 02 Offload sync reads to Aurora reader endpoints to avoid load on the writer instance.
  • 03 Sync CRM or ERP records into a Cosmos DB container that backs a customer-facing application.
  • 04 Mirror Cosmos DB items into Postgres so teams can query operational data with standard SQL.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both Amazon Aurora and Azure Cosmos DB, 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.

Shared reference data between services

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

What you can sync between Amazon Aurora and Azure Cosmos DB

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 Azure Cosmos DB objects How this pairing syncs
Databases Logical databases within a cluster that scope a sync connection. Databases Top-level namespaces that scope containers and throughput provisioning. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Stored procedures and triggers Server-side logic scoped to a partition; relevant when writes must respect existing validation. Schemas is specific to Amazon Aurora and Stored procedures and triggers to Azure Cosmos DB — each maps to any object or custom field on the other side.
Tables Relational tables synced bi-directionally at row level. Containers The unit of partitioning and throughput; each container maps to a synced collection. Tables is specific to Amazon Aurora and Containers to Azure Cosmos DB — each maps to any object or custom field on the other side.
Views Read-only query-backed sources for downstream syncs. Items (JSON documents) Schema-flexible JSON records read and written during sync; nested structures are flattened or mapped as needed. Views is specific to Amazon Aurora and Items (JSON documents) to Azure Cosmos DB — each maps to any object or custom field on the other side.
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Partition keys Determine data distribution and must be included on writes for the sync to route items correctly. Materialized Views is specific to Amazon Aurora and Partition keys to Azure Cosmos DB — each maps to any object or custom field on the other side.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Change feed entries Ordered record of inserts and updates per partition, consumed for incremental sync. Columns and Data Types is specific to Amazon Aurora and Change feed entries to Azure Cosmos DB — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora and Azure Cosmos DB

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 Azure Cosmos DB 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 Azure Cosmos DB as a row-level write, with types converted between the two schemas.

Azure Cosmos DB Amazon Aurora Sub-second propagation

DetectionChanges in Azure Cosmos DB are captured at the source via change data capture — no polling loop against its API. Built-in change feed exposing inserts and updates in order within each partition key range.

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 ⇄ Azure Cosmos DB

Connect Amazon Aurora and Azure Cosmos DB for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora or Azure Cosmos DB 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 Azure Cosmos DB record.

Observability

Monitoring

Track your Amazon Aurora ⇄ Azure Cosmos DB 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 Azure Cosmos DB.

How the Amazon Aurora and Azure Cosmos DB 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

Azure Cosmos DB

Integration surface
REST API and SDKs over HTTPS (API for NoSQL, formerly the SQL API); also MongoDB, Cassandra, Gremlin, and Table API surfaces
Authentication
Account keys, resource tokens, or Microsoft Entra ID role-based access
Change detection
Built-in change feed exposing inserts and updates in order within each partition key range
Capabilities
read · write · CDC
How it works

How to connect Amazon Aurora to Azure Cosmos DB — 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 Azure Cosmos DB 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
    Azure Cosmos DB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon Aurora and Azure Cosmos DB 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 ⇄ Azure Cosmos DB
    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 Azure Cosmos DB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Aurora and Azure Cosmos DB 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
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 368 integrations available for Amazon Aurora and Azure Cosmos DB.

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All Amazon Aurora integrations All Azure Cosmos DB integrations Browse all integrations
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