Real-time
Two-way sync
Changes in PostgreSQL or Rabbitmq instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Developer tools
PostgreSQL to Rabbitmq integration — real-time, two-way sync
Keep PostgreSQL and Rabbitmq 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
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect PostgreSQL and Rabbitmq
Keep PostgreSQL and Rabbitmq in step: the rows in your database and the Users and Permissions, Nodes, Queues, Exchanges your engineering tools track stay consistent in real time, in both directions.
PostgreSQL is where your application's durable data lives; Rabbitmq is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.
Stacksync syncs Materialized Views, Schemas, Columns, Primary and Unique Keys in PostgreSQL with Users and Permissions, Nodes, Queues, Exchanges in Rabbitmq field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.
Common use cases
- 01 Expose SaaS objects (CRM contacts, ERP invoices, support tickets) as Postgres tables that internal tools can query and join
- 02 Let an application write to its own database and have those rows appear as records in business systems in near real time
- 03 Route Messages by routing key through a topic Exchange so only Bindings matching a pattern (e.g. region or entity type) trigger a sync.
- 04 Bridge a legacy application that emits AMQP Messages into a warehouse by consuming its Queue and mapping message fields to columns.
Common sync patterns
Where Rabbitmq manages users or groups: keep identity aligned
Directory and identity records in Rabbitmq stay matched to the users or owners table in PostgreSQL, so provisioning and de-provisioning flow from one source.
Turn rows into the records your tools track
A new or changed row in PostgreSQL creates or updates the matching record in Rabbitmq, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
Land tool activity as queryable rows
Records and events from Rabbitmq arrive in PostgreSQL as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
What you can sync between PostgreSQL and Rabbitmq
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.
| PostgreSQL objects | Rabbitmq objects | How this pairing syncs | |
|---|---|---|---|
| Views Read-side projections used to expose joined or filtered data to a sync. | Queues Buffers that store and forward messages; Stacksync consumes from a queue as a source and can declare or write to one as a destination. | Views is specific to PostgreSQL and Queues to Rabbitmq — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed result sets synced outward on a refresh schedule. | Exchanges Routing entry points (direct, fanout, topic, headers); Stacksync publishes messages to an exchange, which forwards copies to bound queues. | Materialized Views is specific to PostgreSQL and Exchanges to Rabbitmq — each maps to any object or custom field on the other side. | |
| Schemas Namespaces that scope which tables a sync reads and writes. | Bindings Rules linking an exchange to a queue by routing key or pattern; they determine which messages reach which queue and can be declared during setup. | Schemas is specific to PostgreSQL and Bindings to Rabbitmq — each maps to any object or custom field on the other side. | |
| Columns Field-level mapping targets; types are mapped to the connected system's field types. | Messages The payload plus headers and properties; consumed (read) via basic.consume and published (write) via basic.publish, then mapped to rows or records. | Columns is specific to PostgreSQL and Messages to Rabbitmq — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. | Virtual Hosts Isolated namespaces (vhosts) that separate environments or tenants; a connection targets one vhost and permissions are scoped to it. | Primary and Unique Keys is specific to PostgreSQL and Virtual Hosts to Rabbitmq — each maps to any object or custom field on the other side. | |
| JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | Consumers Subscriptions registered on a queue for push delivery; RabbitMQ pushes each enqueued message down the consumer's open AMQP connection in real time. | JSONB Columns is specific to PostgreSQL and Consumers to Rabbitmq — each maps to any object or custom field on the other side. |
How changes propagate between PostgreSQL and Rabbitmq
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.
PostgreSQL Rabbitmq Sub-second propagation
DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.
DeliveryEach detected change is written to Rabbitmq through its API, with automatic retries and rate-limit backoff.
Rabbitmq PostgreSQL Interval-based propagation
DetectionStacksync polls Rabbitmq for changes on an incremental schedule, reading only records changed since the previous pass. Push delivery — a consumer subscribes to a queue (AMQP basic.consume) and RabbitMQ pushes each enqueued message down the open AMQP connection in real.
DeliveryEach detected change is applied to PostgreSQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
- Rabbitmq: No fixed API request quota; the broker applies TCP back-pressure (flow control), per-consumer prefetch (QoS) limits, and blocks publishers when memory or disk alarms trip.
What ships with PostgreSQL ⇄ Rabbitmq
Connect PostgreSQL and Rabbitmq for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every PostgreSQL–Rabbitmq connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever PostgreSQL or Rabbitmq 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 PostgreSQL or Rabbitmq record.
Observability
Monitoring
Track your PostgreSQL ⇄ Rabbitmq sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between PostgreSQL and Rabbitmq.
How the PostgreSQL and Rabbitmq connectors work
PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL frontend/backend protocol)
- Authentication
- Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
- Change detection
- Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
Rabbitmq
- Integration surface
- AMQP 0-9-1 for publish/consume (AMQP 1.0 is native in RabbitMQ 4.0+; MQTT and STOMP via plugins) plus the Management HTTP REST API on port 15672
- Authentication
- AMQP username/password (SASL PLAIN) over TLS, plus x509 client certificates and OAuth 2.0 (JWT) via auth-backend plugins; the Management HTTP API uses HTTP Basic auth, or Bearer tokens when OAuth 2.0 is enabled
- Change detection
- Push delivery — a consumer subscribes to a queue (AMQP basic.consume) and RabbitMQ pushes each enqueued message down the open AMQP connection in real time; there is no modified-date polling, and the Management HTTP API is stats-only and poll-based
- Capabilities
- read · write
- Rate limits
- No fixed API request quota; the broker applies TCP back-pressure (flow control), per-consumer prefetch (QoS) limits, and blocks publishers when memory or disk alarms trip.
How it works
How to connect PostgreSQL to Rabbitmq — 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 PostgreSQL and Rabbitmq with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
PostgreSQL
connected
Rabbitmq
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the PostgreSQL and Rabbitmq 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 · PostgreSQL ⇄ RabbitmqCustomers 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.
PostgreSQL RabbitmqCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
PostgreSQL and Rabbitmq integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between PostgreSQL and Rabbitmq: authenticate both systems, choose the objects to sync (such as PostgreSQL's Views and Materialized Views), 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 PostgreSQL and Rabbitmq. 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 PostgreSQL: Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where. On Rabbitmq: Push delivery — a consumer subscribes to a queue (AMQP basic.consume) and RabbitMQ pushes each enqueued message down the open AMQP connection in real time; there is no modified-date polling, and the Management HTTP API is stats-only and poll-based. 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 PostgreSQL side: Materialized Views, Schemas, Columns, Primary and Unique Keys, plus custom fields where PostgreSQL exposes them. On the Rabbitmq side: Users and Permissions, Nodes, Queues, Exchanges. 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 PostgreSQL and Rabbitmq: Where Rabbitmq manages users or groups: keep identity aligned; Turn rows into the records your tools track; Land tool activity as queryable rows. Directory and identity records in Rabbitmq stay matched to the users or owners table in PostgreSQL, so provisioning and de-provisioning flow from one source.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 424 integrations available for PostgreSQL and Rabbitmq.
Popular · 8 of 424
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PostgreSQL ⇄ Datadog -
PostgreSQL ⇄ Google Pubsub -
PostgreSQL ⇄ Ldap -
PostgreSQL ⇄ Microsoft Graph -
Rabbitmq ⇄ Azure SQL Database -
Rabbitmq ⇄ Citus -
Rabbitmq ⇄ Couchbase -
Rabbitmq ⇄ DuckDB
No integrations match .
