Real-time
Two-way sync
Changes in Citus or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Database
Citus to Postgres Heroku integration — real-time, two-way sync
Keep Citus 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 Citus and Postgres Heroku
Keep Citus and Postgres Heroku synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Citus and Postgres Heroku continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.
- Consolidate per-tenant rows from distributed tables into per-customer reporting databases.
- 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
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both Citus and Postgres Heroku, so each workload runs on the engine that suits it.
What you can sync between Citus 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.
| Citus objects | Postgres Heroku objects | |
|---|---|---|
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Views Read-side projections exposed to outbound syncs. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | Materialized Views Precomputed result sets synced outward on refresh. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Sequences Generate surrogate keys for rows created by inbound syncs. |
What ships with Citus ⇄ Postgres Heroku
Connect Citus and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus 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 Citus or Postgres Heroku record.
Observability
Monitoring
Track your Citus ⇄ 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 Citus and Postgres Heroku.
How the Citus and Postgres Heroku connectors work
Citus
- Integration surface
- PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
- Authentication
- Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
- Change detection
- PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
- 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 Citus 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 Citus 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.
Citus
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus 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 · Citus ⇄ 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.
Citus Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Postgres Heroku integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Citus and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Citus's Schemas and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Citus and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Citus–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both Citus 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 Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. 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 Citus side: Distributed tables, Reference tables, Local tables, Schemas, plus custom fields where Citus exposes them. On the Postgres Heroku side: JSONB Columns, Sequences, Follower Databases, Tables. 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.
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 Citus and Postgres Heroku.
Popular · 8 of 386
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Citus ⇄ Amazon Lightsail -
Citus ⇄ Apache Cassandra -
Citus ⇄ Azure Cosmos DB -
Citus ⇄ Azure SQL Database -
Postgres Heroku ⇄ SingleStore -
Postgres Heroku ⇄ Amazon Aurora - Postgres Heroku ⇄ Amazon Lightsail
- Postgres Heroku ⇄ Apache Cassandra
No integrations match .
