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Database ⇄ Data warehouse

Postgres Heroku to Snowflake integration — real-time, two-way sync

Keep Postgres Heroku and Snowflake 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 Postgres Heroku and Snowflake

Connect Postgres Heroku and Snowflake 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 Snowflake, 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 Snowflake in real time, and result tables in Snowflake sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.

Common use cases

  • Feed finance reconciliation models from ERP data landed in Snowflake on a continuous basis
  • Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL
  • Reflect billing and subscription records into the app database so product logic reads local rows
  • Expose CRM objects as Postgres tables the Heroku application can query and join directly

Operational data in the warehouse, minus the pipeline

Rows from Postgres Heroku land in Snowflake as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Snowflake 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.

What you can sync between Postgres Heroku and Snowflake

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.

Postgres Heroku objects Snowflake objects
Sequences Generate surrogate keys for rows created by inbound syncs. Schemas Namespaces within a database used to organize synced tables.
Follower Databases Heroku-managed read replicas usable as low-impact sync sources. Tables The main landing and activation target for synced records.
Tables Standard Postgres tables; the primary two-way sync target for app data. Views Modeled projections used as the source side of outbound syncs.
Views Read-side projections exposed to outbound syncs. Materialized Views Precomputed results synced outward for low-latency reads.
Materialized Views Precomputed result sets synced outward on refresh. Streams Row-level change records on a table, consumed to process deltas instead of full scans.
Schemas Namespaces that scope which tables a sync reads and writes. Stages File staging areas used for bulk loads into synced tables.
What ships with Postgres Heroku ⇄ Snowflake

Connect Postgres Heroku and Snowflake for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Postgres Heroku or Snowflake instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Postgres Heroku or Snowflake 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 Postgres Heroku or Snowflake record.

Observability

Monitoring

Track your Postgres Heroku ⇄ Snowflake sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Postgres Heroku and Snowflake.

How the Postgres Heroku and Snowflake connectors work

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

Snowflake

Integration surface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
Capabilities
read · write · CDC
Rate limits
No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
Snowflake setup guide
How it works

How to connect Postgres Heroku to Snowflake — 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 Postgres Heroku and Snowflake 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
    Postgres Heroku connected
    Snowflake connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Postgres Heroku and Snowflake 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 · Postgres Heroku ⇄ Snowflake
    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
    Postgres Heroku Snowflake
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Postgres Heroku and Snowflake integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for Postgres Heroku and Snowflake.

Popular · 8 of 386
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