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Data warehouse

Amazon Redshift to Azure Synapse Analytics integration — real-time, two-way sync

Keep Amazon Redshift and Azure Synapse Analytics 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 Amazon Redshift and Azure Synapse Analytics

Keep tables consistent across Amazon Redshift and Azure Synapse Analytics, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.

Stacksync syncs tables between Amazon Redshift and Azure Synapse Analytics continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.

Common use cases

  • 01 Publish finance rollups computed in Redshift back to spreadsheets or operational tools.
  • 02 Feed customer 360 tables built in Redshift to support and success platforms.
  • 03 Sync curated Synapse views into an operational Postgres or Azure SQL database that applications can query cheaply.
  • 04 Consolidate SaaS data alongside lake data so analysts join both through one SQL surface.

Common sync patterns

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

What you can sync between Amazon Redshift and Azure Synapse Analytics

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 Redshift objects Azure Synapse Analytics objects How this pairing syncs
Schemas Namespaces used to organize synced tables and control grants. Schemas Namespaces that separate staging, integration, and presentation layers. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views SQL views readable as modeled sources for reverse syncs. Views Curated projections used when downstream tools should not read base tables directly. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Materialized Views Precomputed results that downstream syncs can read for performance. Materialized views Precomputed aggregates that speed reads of frequently synced result sets. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Stored Procedures SQL procedures sometimes invoked around load steps. SQL pools Dedicated or serverless compute contexts that determine how and where queries run. Stored Procedures is specific to Amazon Redshift and SQL pools to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Users and Groups Principals used to grant a sync connection scoped access. Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. Users and Groups is specific to Amazon Redshift and Tables (dedicated SQL pool) to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Databases Top-level containers within a cluster or serverless workgroup. External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. Databases is specific to Amazon Redshift and External tables to Azure Synapse Analytics — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift and Azure Synapse Analytics

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 Redshift Azure Synapse Analytics Interval-based propagation

DetectionStacksync polls Amazon Redshift for changes on an incremental schedule, reading only records changed since the previous pass. Polling or query-based diffing.

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

Azure Synapse Analytics Amazon Redshift Interval-based propagation

DetectionStacksync polls Azure Synapse Analytics for changes on an incremental schedule, reading only records changed since the previous pass. Polling on watermark columns.

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

Rate-limit considerations

  • Amazon Redshift: Bounded by cluster or serverless capacity and concurrency settings rather than API quotas.
What ships with Amazon Redshift ⇄ Azure Synapse Analytics

Connect Amazon Redshift and Azure Synapse Analytics for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–Azure Synapse Analytics connection.

Real-time

Two-way sync

Changes in Amazon Redshift or Azure Synapse Analytics instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Redshift or Azure Synapse Analytics 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 Redshift or Azure Synapse Analytics record.

Observability

Monitoring

Track your Amazon Redshift ⇄ Azure Synapse Analytics sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Redshift and Azure Synapse Analytics.

How the Amazon Redshift and Azure Synapse Analytics connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

Azure Synapse Analytics

Integration surface
SQL wire protocol (TDS) with T-SQL for SQL pools; additional Spark and pipeline surfaces exist but syncs use the SQL endpoint
Authentication
SQL authentication or Microsoft Entra ID
Change detection
Polling on watermark columns; Synapse SQL pools do not expose log-based CDC for downstream consumers
Capabilities
read · write
How it works

How to connect Amazon Redshift to Azure Synapse Analytics — 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 Redshift and Azure Synapse Analytics 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 Redshift connected
    Azure Synapse Analytics connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon Redshift and Azure Synapse Analytics 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 Redshift ⇄ Azure Synapse Analytics
    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 Redshift Azure Synapse Analytics
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Redshift and Azure Synapse Analytics 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 577 integrations available for Amazon Redshift and Azure Synapse Analytics.

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