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Data warehouse ⇄ Database

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

Keep Azure Synapse Analytics and Postgres Heroku 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 Azure Synapse Analytics and Postgres Heroku

Connect Postgres Heroku and Azure Synapse Analytics with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Postgres Heroku's rows in Azure Synapse Analytics, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Postgres Heroku where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Postgres Heroku sync into Azure Synapse Analytics in real time, and result tables in Azure Synapse Analytics sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Load CRM and ERP records into Synapse dedicated SQL pool tables for enterprise reporting.
  • 02 Publish warehouse aggregates (account health scores, LTV) from Synapse back into operational tools like a CRM.
  • 03 Expose CRM objects as Postgres tables the Heroku application can query and join directly
  • 04 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos

Common sync patterns

Serve warehouse results at database speed

Aggregates or model outputs computed in Azure Synapse Analytics sync into Postgres Heroku, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in Azure Synapse Analytics and keep Postgres Heroku focused on its operational workload.

What you can sync between Azure Synapse Analytics and Postgres Heroku

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 Postgres Heroku objects How this pairing syncs
Views Curated projections used when downstream tools should not read base tables directly. Views Read-side projections exposed to outbound syncs. 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. Schemas Namespaces that scope which tables a sync reads and writes. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Materialized views Precomputed aggregates that speed reads of frequently synced result sets. Materialized Views Precomputed result sets synced outward on refresh. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. Tables (dedicated SQL pool) is specific to Azure Synapse Analytics and JSONB Columns to Postgres Heroku — 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. Sequences Generate surrogate keys for rows created by inbound syncs. External tables is specific to Azure Synapse Analytics and Sequences to Postgres Heroku — 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. Follower Databases Heroku-managed read replicas usable as low-impact sync sources. SQL pools is specific to Azure Synapse Analytics and Follower Databases to Postgres Heroku — each maps to any object or custom field on the other side.

How changes propagate between Azure Synapse Analytics and Postgres Heroku

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

Postgres Heroku Azure Synapse Analytics Interval-based propagation

DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.

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

Rate-limit considerations

  • Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Azure Synapse Analytics ⇄ Postgres Heroku

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

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

Real-time

Two-way sync

Changes in Azure Synapse Analytics or Postgres Heroku 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 Postgres Heroku 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 Postgres Heroku record.

Observability

Monitoring

Track your Azure Synapse Analytics ⇄ Postgres Heroku 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 Postgres Heroku.

How the Azure Synapse Analytics and Postgres Heroku 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

Postgres Heroku

Integration surface
SQL wire protocol (standard PostgreSQL)
Authentication
Database credentials from the Heroku DATABASE_URL config var; SSL required
Change detection
Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
Capabilities
read · write
Rate limits
No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works

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

    Choose tables

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

Azure Synapse Analytics and Postgres Heroku 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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→ 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 483 integrations available for Azure Synapse Analytics and Postgres Heroku.

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