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Amazon DynamoDB to Azure SQL Database integration — real-time, two-way sync

Keep Amazon DynamoDB and Azure SQL Database 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 SQL Database

Keep Amazon DynamoDB and Azure SQL Database 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 SQL Database 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 Replicate Azure SQL tables to a warehouse without building custom CDC pipelines.
  • 04 Consolidate data from several line-of-business apps into one Azure SQL database as an integration hub.

Common sync patterns

Regional or environment copies

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

Cross-engine sync

Keep the same dataset live in both Amazon DynamoDB and Azure SQL Database, 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.

What you can sync between Amazon DynamoDB and Azure SQL Database

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 SQL Database objects How this pairing syncs
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. Tables The primary sync target; rows map one-to-one to records in the paired system. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Time to Live (TTL) Per-item expiry timestamps; DynamoDB deletes expired items in the background and emits a Streams REMOVE record for each deletion. Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Time to Live (TTL) is specific to Amazon DynamoDB and Views to Azure SQL Database — 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. Schemas Namespaces that organize tables and control which objects a sync user can reach. Items is specific to Amazon DynamoDB and Schemas to Azure SQL Database — 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. Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Rows and columns to Azure SQL Database — each maps to any object or custom field on the other side.
Local secondary indexes (LSIs) Extra sort keys within the same partition key, defined at table creation; queried like the base table for alternate access patterns. Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Stored procedures to Azure SQL Database — each maps to any object or custom field on the other side.
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. Change tracking / CDC tables System-maintained change records used to drive incremental sync. DynamoDB Streams is specific to Amazon DynamoDB and Change tracking / CDC tables to Azure SQL Database — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and Azure SQL Database

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

Azure SQL Database Amazon DynamoDB Sub-second propagation

DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.

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 SQL Database

Connect Amazon DynamoDB and Azure SQL Database for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Amazon DynamoDB or Azure SQL Database 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 SQL Database 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 SQL Database record.

Observability

Monitoring

Track your Amazon DynamoDB ⇄ Azure SQL Database 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 SQL Database.

How the Amazon DynamoDB and Azure SQL Database 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 SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC
How it works

How to connect Amazon DynamoDB to Azure SQL Database — 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 SQL Database 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 SQL Database connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon DynamoDB and Azure SQL Database 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 SQL Database
    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 SQL Database
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon DynamoDB and Azure SQL Database 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 475 integrations available for Amazon DynamoDB and Azure SQL Database.

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