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Data warehouse

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

Keep Azure Synapse Analytics and Materialize 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

Case study
Migrated from MuleSoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Azure Synapse Analytics and Materialize

Keep tables consistent across Azure Synapse Analytics and Materialize, 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 Azure Synapse Analytics and Materialize 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 Sync curated Synapse views into an operational Postgres or Azure SQL database that applications can query cheaply.
  • 02 Consolidate SaaS data alongside lake data so analysts join both through one SQL surface.
  • 03 Bridge streaming sources and non-streaming destinations by materializing joins across both.
  • 04 Sync operational CRM or ERP data into Materialize so real-time views stay current without batch loads.

Common sync patterns

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.

Serve tools that only connect to one platform

Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.

What you can sync between Azure Synapse Analytics and Materialize

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.

Azure Synapse Analytics objects Materialize objects How this pairing syncs
Materialized views Precomputed aggregates that speed reads of frequently synced result sets. Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces that separate staging, integration, and presentation layers. Clusters Compute pools that isolate ingestion, view maintenance, and serving. Schemas is specific to Azure Synapse Analytics and Clusters to Materialize — each maps to any object or custom field on the other side.
SQL pools Dedicated or serverless compute contexts that determine how and where queries run. Connections & Secrets Stored credentials and endpoints used by sources and sinks. SQL pools is specific to Azure Synapse Analytics and Connections & Secrets to Materialize — each maps to any object or custom field on the other side.
Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. Schemas & Databases Namespaces that organize objects a sync targets. Tables (dedicated SQL pool) is specific to Azure Synapse Analytics and Schemas & Databases to Materialize — each maps to any object or custom field on the other side.
External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. External tables is specific to Azure Synapse Analytics and Tables to Materialize — each maps to any object or custom field on the other side.
Views Curated projections used when downstream tools should not read base tables directly. Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. Views is specific to Azure Synapse Analytics and Sources to Materialize — each maps to any object or custom field on the other side.

How changes propagate between Azure Synapse Analytics and Materialize

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.

Azure Synapse Analytics Materialize 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 Materialize as a row-level write, with types converted between the two schemas.

Materialize Azure Synapse Analytics Sub-second propagation

DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.

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

What ships with Azure Synapse Analytics ⇄ Materialize

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure Synapse Analytics or Materialize 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 Azure Synapse Analytics or Materialize record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Azure Synapse Analytics and Materialize connectors work

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

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

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

    Choose tables

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

Azure Synapse Analytics and Materialize 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 472 integrations available for Azure Synapse Analytics and Materialize.

Popular · 5 of 472
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