Two-way sync
Changes in Azure Service Bus or Materialize instantly reflect in both systems. No stale data, no manual imports.
Keep Azure Service Bus and Materialize in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Materialize is the central store where teams keep Clusters, Connections & Secrets, Schemas & Databases, Tables for reporting and analysis; Azure Service Bus runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Queues, Topics, Subscriptions, Messages produced in Azure Service Bus are exactly what analysts want to measure in Materialize, and the curated rows in Materialize are what should drive the next action in Azure Service Bus. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.
Stacksync syncs Clusters, Connections & Secrets, Schemas & Databases, Tables in Materialize with Queues, Topics, Subscriptions, Messages in Azure Service Bus field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.
Records created in Azure Service Bus — issues, events, messages, metrics, or user changes — replicate into Materialize tables as they happen, so reporting runs on current data instead of last night's export.
A row scored, flagged, or enriched in Materialize creates or updates the matching record in Azure Service Bus, so the operational tool acts on the same data the analysts already see.
Load the existing set of Queues, Topics, Subscriptions, Messages into Materialize once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.
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 | Materialize objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Rules / Filters is specific to Azure Service Bus and Materialized Views to Materialize — 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. | Sinks Outbound connections that emit view changes to Kafka topics. | Sessions is specific to Azure Service Bus and Sinks to Materialize — 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. | Indexes In-memory arrangements that make view reads fast for serving workloads. | Dead-letter queue is specific to Azure Service Bus and Indexes to Materialize — 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. | Clusters Compute pools that isolate ingestion, view maintenance, and serving. | Scheduled / deferred messages is specific to Azure Service Bus and Clusters to Materialize — 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. | Connections & Secrets Stored credentials and endpoints used by sources and sinks. | Queues is specific to Azure Service Bus and Connections & Secrets to Materialize — 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. | Schemas & Databases Namespaces that organize objects a sync targets. | Topics is specific to Azure Service Bus and Schemas & Databases to Materialize — each maps to any object or custom field on the other side. |
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.
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 Materialize as a row-level write, with types converted between the two schemas.
DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.
DeliveryEach detected change is written to Azure Service Bus through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Service Bus–Materialize connection.
Changes in Azure Service Bus or Materialize instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure Service Bus or Materialize data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Azure Service Bus or Materialize record.
Track your Azure Service Bus ⇄ Materialize sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure Service Bus and Materialize.
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.
Authenticate Azure Service Bus and Materialize with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Azure Service Bus and Materialize 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Azure Service Bus and Materialize: authenticate both systems, choose the objects to sync (such as Azure Service Bus's Rules / Filters and Sessions), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Azure Service Bus and Materialize: Operational data lands in Materialize for analytics; Warehouse signals reach Azure Service Bus; Backfill history, then stay live. Records created in Azure Service Bus — issues, events, messages, metrics, or user changes — replicate into Materialize tables as they happen, so reporting runs on current data instead of last night's export.
Azure Service Bus: 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. Materialize: PostgreSQL wire protocol (SQL). Authentication: Database credentials (username/password; app passwords in the managed cloud service). Stacksync manages authentication, retries, and rate limits on both sides.
Materialize: Views are maintained incrementally as data arrives rather than recomputed at query time, which is what makes reads consistently fresh. 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 Materialize without custom code.
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 Materialize records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Azure Service Bus and Materialize connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Service Bus–Materialize integration in-house.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 316 integrations available for Azure Service Bus and Materialize.