Real-time
Two-way sync
Changes in Azure Service Bus or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Database
Azure Service Bus to Neo4j integration — real-time, two-way sync
Keep Azure Service Bus and Neo4j 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 Neo4j
Keep Neo4j and Azure Service Bus in step: the rows in your database and the Topics, Subscriptions, Messages, Rules / Filters your engineering tools track stay consistent in real time, in both directions.
Neo4j 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 Relationships, Properties, Labels, Indexes & Constraints in Neo4j with Topics, Subscriptions, Messages, Rules / Filters 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 Write computed relationship scores (fraud, influence, similarity) back to operational systems.
- 02 Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
- 03 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.
- 04 Fan out CRM or ERP record changes to a topic and let billing, analytics, and notification subscriptions each filter with SQL rules and react without coupling to the source.
Common sync patterns
One integration pattern instead of per-tool API code
Read and write the synced tables in Neo4j 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 Neo4j, and writes to Neo4j propagate to Azure Service Bus within seconds, so triggers, jobs, and alerts fire without polling.
Where Azure Service Bus manages users or groups: keep identity aligned
Directory and identity records in Azure Service Bus stay matched to the users or owners table in Neo4j, so provisioning and de-provisioning flow from one source.
What you can sync between Azure Service Bus and Neo4j
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 | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Relationships Typed, directed edges that carry the connections syncs exist to model. | Queues is specific to Azure Service Bus and Relationships to Neo4j — 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. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Topics is specific to Azure Service Bus and Properties to Neo4j — 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. | Labels Node type markers used to map source tables or objects onto the graph. | Subscriptions is specific to Azure Service Bus and Labels to Neo4j — each maps to any object or custom field on the other side. | |
| Messages The synced unit: a body plus system and user properties, MessageId, SessionId, and TTL; capped at 256 KB on Standard and up to 100 MB on Premium over AMQP. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | Messages is specific to Azure Service Bus and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side. | |
| Rules / Filters SQL or correlation filters on a subscription that decide which topic messages it receives; a rule can also add or modify properties via a filter action. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Rules / Filters is specific to Azure Service Bus and Databases to Neo4j — each maps to any object or custom field on the other side. | |
| 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. | Users & Roles Security principals controlling what an integration credential can query or modify. | Sessions is specific to Azure Service Bus and Users & Roles to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Azure Service Bus and Neo4j
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 Neo4j 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 written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Azure Service Bus Sub-second propagation
DetectionChanges in Neo4j are captured at the source via change data capture — no polling loop against its API. Neo4j Change Data Capture on Enterprise and Aura streams graph changes.
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 ⇄ Neo4j
Connect Azure Service Bus and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Service Bus–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Azure Service Bus or Neo4j 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 Neo4j record.
Observability
Monitoring
Track your Azure Service Bus ⇄ Neo4j 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 Neo4j.
How the Azure Service Bus and Neo4j 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
Neo4j
- Integration surface
- Bolt binary protocol with Cypher via official drivers, plus an HTTP query API
- Authentication
- Username/password (basic auth); enterprise deployments add SSO options
- Change detection
- Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties
- Capabilities
- read · write · CDC
How it works
How to connect Azure Service Bus to Neo4j — 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 Neo4j 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
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Azure Service Bus and Neo4j 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 ⇄ Neo4jCustomers 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 Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Azure Service Bus and Neo4j integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Azure Service Bus and Neo4j: authenticate both systems, choose the objects to sync (such as Azure Service Bus's Queues and Topics), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 Neo4j 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 Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Service Bus–Neo4j integration in-house.
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Yes — Stacksync ships production-grade connectors for both Azure Service Bus and Neo4j. 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 Neo4j: Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties. 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 Neo4j side: Relationships, Properties, Labels, Indexes & Constraints, plus custom fields where Neo4j exposes them. On the Azure Service Bus side: Topics, Subscriptions, Messages, Rules / Filters. Stacksync auto-detects both schemas and converts types between the two systems.
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 396 integrations available for Azure Service Bus and Neo4j.
Popular · 8 of 396
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Azure Service Bus ⇄ Citus -
Azure Service Bus ⇄ Couchbase -
Azure Service Bus ⇄ DuckDB -
Azure Service Bus ⇄ Elasticsearch -
Neo4j ⇄ Rabbitmq -
Neo4j ⇄ Datadog -
Neo4j ⇄ Google Pubsub -
Neo4j ⇄ Ldap
No integrations match .
