Real-time
Two-way sync
Changes in Azure Service Bus or Citus instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Database
Azure Service Bus to Citus integration — real-time, two-way sync
Keep Azure Service Bus and Citus 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 Service Bus and Citus
Keep Citus and Azure Service Bus in step: the rows in your database and the Dead-letter queue, Scheduled / deferred messages, Queues, Topics your engineering tools track stay consistent in real time, in both directions.
Citus is where your application's durable data lives; Azure Service Bus 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 Views, Sequences, Distributed tables, Reference tables in Citus with Dead-letter queue, Scheduled / deferred messages, Queues, Topics in Azure Service Bus 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 Consolidate per-tenant rows from distributed tables into per-customer reporting databases.
- 02 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
- 03 Send new and changed database rows as messages to a Service Bus queue or topic so multiple downstream consumers process the change stream independently.
- 04 Receive messages from a queue or subscription with an AMQP receiver and write them into a Postgres or warehouse table for durable, SQL-queryable storage.
Common sync patterns
Land tool activity as queryable rows
Records and events from Azure Service Bus arrive in Citus as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
One integration pattern instead of per-tool API code
Read and write the synced tables in Citus and Stacksync keeps Azure Service Bus current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.
React to changes on either side in near real time
Updates in Azure Service Bus arrive as row changes in Citus, and writes to Citus propagate to Azure Service Bus within seconds, so triggers, jobs, and alerts fire without polling.
What you can sync between Azure Service Bus and Citus
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 Service Bus objects | Citus objects | How this pairing syncs | |
|---|---|---|---|
| Sessions Message sessions group related messages by SessionId so one consumer handles them in FIFO order; the way ordered processing is achieved in Service Bus. | Views Curated projections over distributed data, often used as read-only sync sources. | Sessions is specific to Azure Service Bus and Views to Citus — each maps to any object or custom field on the other side. | |
| Dead-letter queue A sub-queue on every queue and subscription that automatically holds messages exceeding the max delivery count or their TTL, read for inspection and reprocessing. | Sequences Key generators that matter when external writes must not collide with application inserts. | Dead-letter queue is specific to Azure Service Bus and Sequences to Citus — each maps to any object or custom field on the other side. | |
| Scheduled / deferred messages Messages enqueued for future delivery at a set time, or deferred and set aside by sequence number for retrieval later, out of the normal receive order. | Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Scheduled / deferred messages is specific to Azure Service Bus and Distributed tables to Citus — each maps to any object or custom field on the other side. | |
| Queues Point-to-point entity: a sender writes messages and one competing consumer at a time receives them under PeekLock, then completes or abandons each message. | Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Queues is specific to Azure Service Bus and Reference tables to Citus — each maps to any object or custom field on the other side. | |
| Topics Publish/subscribe entity a publisher sends to; each message is fanned out to every subscription whose filter rules match, so many consumers get their own copy. | Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Topics is specific to Azure Service Bus and Local tables to Citus — each maps to any object or custom field on the other side. | |
| Subscriptions A virtual queue attached to a topic; a consumer receives its own stream of matching messages here, independent of other subscriptions on the same topic. | Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Subscriptions is specific to Azure Service Bus and Schemas to Citus — each maps to any object or custom field on the other side. |
How changes propagate between Azure Service Bus and Citus
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 Service Bus Citus Interval-based propagation
DetectionStacksync polls Azure Service Bus for changes on an incremental schedule, reading only records changed since the previous pass. Consumes messages as they arrive: an AMQP receiver holds an open connection and takes messages with PeekLock (lock, then complete/abandon) or.
DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.
Citus Azure Service Bus Sub-second propagation
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is written to Azure Service Bus through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Azure Service Bus: Standard tier throttles around 1,000 operations/second and returns a ServerBusy error; Premium provisions dedicated messaging units (1, 2, 4, 8, or 16) for isolated, predictable throughput. Up to 5,000 concurrent AMQP connections per namespace and 5,000 concurrent receive requests per entity.
What ships with Azure Service Bus ⇄ Citus
Connect Azure Service Bus and Citus for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Service Bus–Citus connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Azure Service Bus or Citus 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 Service Bus or Citus record.
Observability
Monitoring
Track your Azure Service Bus ⇄ Citus sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Azure Service Bus and Citus.
How the Azure Service Bus and Citus connectors work
Azure Service Bus
- Integration surface
- AMQP 1.0 messaging protocol plus an HTTP/REST API; entities live under a namespace at <namespace>.servicebus.windows.net (legacy SBMP also supported)
- Authentication
- Microsoft Entra ID (Azure AD) RBAC with managed identities - roles Azure Service Bus Data Owner, Data Sender, and Data Receiver - or Shared Access Signature (SAS) policies scoped with Manage, Send, and Listen claims
- Change detection
- Consumes messages as they arrive: an AMQP receiver holds an open connection and takes messages with PeekLock (lock, then complete/abandon) or ReceiveAndDelete. No modified-date polling and no native HTTP push; Azure Event Grid can separately raise an 'active messages available' event for intermittent receivers
- Capabilities
- read · write
- Rate limits
- Standard tier throttles around 1,000 operations/second and returns a ServerBusy error; Premium provisions dedicated messaging units (1, 2, 4, 8, or 16) for isolated, predictable throughput. Up to 5,000 concurrent AMQP connections per namespace and 5,000 concurrent receive requests per entity
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
How it works
How to connect Azure Service Bus to Citus — 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 Azure Service Bus and Citus with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Azure Service Bus
connected
Citus
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Azure Service Bus and Citus 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 · Azure Service Bus ⇄ CitusCustomers 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.
Azure Service Bus CitusCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Azure Service Bus and Citus integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Azure Service Bus and Citus: authenticate both systems, choose the objects to sync (such as Azure Service Bus's Sessions and Dead-letter queue), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Citus: Distributed tables are sharded by a declared distribution column, and reference tables are fully replicated to all nodes; the table type changes how writes and joins behave. Azure Service Bus: Message size differs by tier: Standard caps messages at 256 KB, while Premium defaults to 1 MB and supports up to 100 MB per message over AMQP; message batches are capped at 1 MB on all tiers. Stacksync's field mapping accounts for these differences between Azure Service Bus and Citus without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Azure Service Bus and Citus records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Azure Service Bus and Citus connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Service Bus–Citus integration in-house.
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Yes — Stacksync ships production-grade connectors for both Azure Service Bus and Citus. 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 Azure Service Bus: Consumes messages as they arrive: an AMQP receiver holds an open connection and takes messages with PeekLock (lock, then complete/abandon) or ReceiveAndDelete. No modified-date polling and no native HTTP push; Azure Event Grid can separately raise an 'active messages available' event for intermittent receivers. On Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 311 integrations available for Azure Service Bus and Citus.
Popular · 7 of 311
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Azure Service Bus ⇄ PostgreSQL -
Azure Service Bus ⇄ Amazon RDS -
Azure Service Bus ⇄ Supabase -
Azure Service Bus ⇄ MySQL -
Citus ⇄ Jms -
Citus ⇄ Newrelic -
Citus ⇄ Opsgenie
No integrations match .
