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

Keep Amazon DynamoDB 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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Why teams connect Amazon DynamoDB and Azure Cosmos DB

Keep Amazon DynamoDB 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 DynamoDB 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 Mirror a high-write DynamoDB table into a relational database so teams can join NoSQL application data against relational tables for reporting.
  • 02 Use DynamoDB Streams as a change-data-capture source to push item INSERT, MODIFY, and REMOVE events into a CRM, search index, or operational database in near-real-time.
  • 03 Stream operational documents from Cosmos DB into a SQL warehouse via the change feed for analytics without hitting request-unit budgets with full scans.
  • 04 Sync CRM or ERP records into a Cosmos DB container that backs a customer-facing application.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both Amazon DynamoDB 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 DynamoDB 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 DynamoDB objects Azure Cosmos DB objects How this pairing syncs
DynamoDB Streams Ordered item-level change records (INSERT, MODIFY, REMOVE) with old/new image views and 24-hour retention; the native change-data-capture source Stacksync reads for near-real-time sync. Stored procedures and triggers Server-side logic scoped to a partition; relevant when writes must respect existing validation. DynamoDB Streams is specific to Amazon DynamoDB and Stored procedures and triggers to Azure Cosmos DB — each maps to any object or custom field on the other side.
Global Tables Multi-region, active-active replicas of a table kept in sync by DynamoDB; each region is read and written locally with last-writer-wins conflict resolution. Databases Top-level namespaces that scope containers and throughput provisioning. Global Tables is specific to Amazon DynamoDB and Databases to Azure Cosmos DB — each maps to any object or custom field on the other side.
Time to Live (TTL) Per-item expiry timestamps; DynamoDB deletes expired items in the background and emits a Streams REMOVE record for each deletion. Containers The unit of partitioning and throughput; each container maps to a synced collection. Time to Live (TTL) is specific to Amazon DynamoDB and Containers to Azure Cosmos DB — each maps to any object or custom field on the other side.
Tables Top-level containers, each with a partition key and optional sort key; Stacksync syncs a table as a stream of items with full read and write via PutItem, UpdateItem, and DeleteItem. Items (JSON documents) Schema-flexible JSON records read and written during sync; nested structures are flattened or mapped as needed. Tables is specific to Amazon DynamoDB and Items (JSON documents) to Azure Cosmos DB — each maps to any object or custom field on the other side.
Items Individual schemaless records (attributes up to 400 KB each); read with GetItem, Query, and Scan and written with PutItem or BatchWriteItem, so write is supported here. Partition keys Determine data distribution and must be included on writes for the sync to route items correctly. Items is specific to Amazon DynamoDB and Partition keys to Azure Cosmos DB — each maps to any object or custom field on the other side.
Global secondary indexes (GSIs) Alternate key projections that let you Query by non-key attributes without a full table Scan; read-only views maintained automatically by DynamoDB. Change feed entries Ordered record of inserts and updates per partition, consumed for incremental sync. Global secondary indexes (GSIs) is specific to Amazon DynamoDB 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 DynamoDB 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 DynamoDB Azure Cosmos DB Sub-second propagation

DetectionChanges in Amazon DynamoDB are captured at the source via change data capture — no polling loop against its API. DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views.

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 DynamoDB 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 DynamoDB as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon DynamoDB: Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.
What ships with Amazon DynamoDB ⇄ Azure Cosmos DB

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

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

Real-time

Two-way sync

Changes in Amazon DynamoDB 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 DynamoDB 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 DynamoDB or Azure Cosmos DB record.

Observability

Monitoring

Track your Amazon DynamoDB ⇄ 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 DynamoDB and Azure Cosmos DB.

How the Amazon DynamoDB and Azure Cosmos DB connectors work

Amazon DynamoDB

Integration surface
AWS SDK / low-level HTTPS JSON API at dynamodb.<region>.amazonaws.com (PutItem, GetItem, UpdateItem, DeleteItem, Query, Scan, BatchWriteItem, TransactWriteItems), plus PartiQL (ExecuteStatement) for SQL-style access and DynamoDB Streams for change capture.
Authentication
AWS Signature Version 4 (SigV4) signed requests using an IAM access key ID and secret key, or temporary STS credentials from an assumed IAM role; IAM policies scope access down to table and item level.
Change detection
DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views and 24-hour retention, read via shard iterators (or Kinesis Data Streams for longer retention). No native HTTP webhooks.
Capabilities
read · write · CDC
Rate limits
Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.

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 DynamoDB 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 DynamoDB 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 DynamoDB connected
    Azure Cosmos DB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Amazon DynamoDB 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.

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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 470 integrations available for Amazon DynamoDB and Azure Cosmos DB.

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