Real-time
Two-way sync
Changes in Materialize or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Materialize to Postgres Heroku integration — real-time, two-way sync
Keep Materialize 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.
- 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
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Materialize and Postgres Heroku
Connect Postgres Heroku and Materialize 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 Materialize, 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 Materialize in real time, and result tables in Materialize sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.
Common use cases
- Read computed view results back into a CRM or application database as derived fields.
- Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
- Keep several Heroku app databases aligned with one system of record
- Reflect billing and subscription records into the app database so product logic reads local rows
Offload heavy reads
Point analytical queries at the synced copy in Materialize and keep Postgres Heroku focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Postgres Heroku land in Materialize as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Materialize sync into Postgres Heroku, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Materialize 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.
| Materialize objects | Postgres Heroku objects | |
|---|---|---|
| Schemas & Databases Namespaces that organize objects a sync targets. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | |
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | |
| Indexes In-memory arrangements that make view reads fast for serving workloads. | Tables Standard Postgres tables; the primary two-way sync target for app data. |
What ships with Materialize ⇄ Postgres Heroku
Connect Materialize and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Materialize 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 Materialize or Postgres Heroku record.
Observability
Monitoring
Track your Materialize ⇄ 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 Materialize and Postgres Heroku.
How the Materialize and Postgres Heroku connectors work
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
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 Materialize 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.
- 01
Connect your apps
Authenticate Materialize 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.
Materialize
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Materialize 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.
objects · Materialize ⇄ Postgres HerokuCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Materialize Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Materialize and Postgres Heroku integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Materialize and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Materialize's Schemas & Databases and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Materialize and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. On Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Materialize side: Sinks, Indexes, Clusters, Connections & Secrets, plus custom fields where Materialize exposes them. On the Postgres Heroku side: Follower Databases, Tables, Views, Materialized Views. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Materialize and Postgres Heroku: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Materialize and keep Postgres Heroku focused on its operational workload.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Materialize and Postgres Heroku.
Popular · 8 of 386
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Materialize ⇄ IBM AS/400 -
Materialize ⇄ IBM Informix -
Materialize ⇄ InfluxDB -
Materialize ⇄ InterSystems IRIS -
Postgres Heroku ⇄ Rockset -
Postgres Heroku ⇄ Starburst Enterprise -
Postgres Heroku ⇄ StarRocks -
Postgres Heroku ⇄ Teradata Vantage
No integrations match .
