Real-time
Two-way sync
Changes in Azure Service Bus or Dremio instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Data warehouse
Azure Service Bus to Dremio integration — real-time, two-way sync
Keep Azure Service Bus and Dremio 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 Dremio
Close the gap between analytics and operations: Dremio holds the record while Azure Service Bus runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.
Dremio is the central store where teams keep Reflections, Jobs, Sources, Physical datasets 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 Topics, Subscriptions, Messages, Rules / Filters produced in Azure Service Bus are exactly what analysts want to measure in Dremio, and the curated rows in Dremio 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 Reflections, Jobs, Sources, Physical datasets in Dremio 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 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.
Common use cases
- 01 Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
- 02 Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
- 03 Preserve per-account or per-order processing order by grouping related messages into a session so a single consumer handles them in FIFO sequence.
- 04 Send new and changed database rows as messages to a Service Bus queue or topic so multiple downstream consumers process the change stream independently.
Common sync patterns
Backfill history, then stay live
Load the existing set of Topics, Subscriptions, Messages, Rules / Filters into Dremio once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.
No batch jobs to babysit
New and changed records move field by field the moment they change, replacing scheduled ETL and one-off scripts that fail quietly and leave stale rows behind.
One shared record, kept consistent
Where both systems track the same entity, a change on either side propagates to the other, ending the manual reconciliation between the operational copy and the warehouse copy.
What you can sync between Azure Service Bus and Dremio
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 | Dremio 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. | Reflections Materialized accelerations that make repeated extraction queries cheaper. | Queues is specific to Azure Service Bus and Reflections to Dremio — 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. | Jobs Query execution records useful for monitoring sync workloads. | Topics is specific to Azure Service Bus and Jobs to Dremio — 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. | Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | Subscriptions is specific to Azure Service Bus and Sources to Dremio — 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. | Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. | Messages is specific to Azure Service Bus and Physical datasets to Dremio — 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. | Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | Rules / Filters is specific to Azure Service Bus and Virtual datasets (views) to Dremio — 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. | Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | Sessions is specific to Azure Service Bus and Apache Iceberg tables to Dremio — each maps to any object or custom field on the other side. |
How changes propagate between Azure Service Bus and Dremio
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 Dremio 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 Dremio as a row-level write, with types converted between the two schemas.
Dremio Azure Service Bus Interval-based propagation
DetectionStacksync polls Dremio for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL.
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.
- Dremio: Bounded by engine capacity and workload management rather than API rate limits.
What ships with Azure Service Bus ⇄ Dremio
Connect Azure Service Bus and Dremio for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Service Bus–Dremio connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Azure Service Bus or Dremio 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 Dremio record.
Observability
Monitoring
Track your Azure Service Bus ⇄ Dremio 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 Dremio.
How the Azure Service Bus and Dremio 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
Dremio
- Integration surface
- Arrow Flight SQL, JDBC/ODBC, and a REST API
- Authentication
- Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
- Change detection
- Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Bounded by engine capacity and workload management rather than API rate limits
How it works
How to connect Azure Service Bus to Dremio — 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 Dremio 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
Dremio
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Azure Service Bus and Dremio 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 ⇄ DremioCustomers 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 DremioCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Azure Service Bus and Dremio integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Azure Service Bus and Dremio: 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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Yes — Stacksync ships production-grade connectors for both Azure Service Bus and Dremio. 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 Dremio: Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed. 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 Dremio side: Reflections, Jobs, Sources, Physical datasets, plus custom fields where Dremio 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.
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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 Azure Service Bus and Dremio: Backfill history, then stay live; No batch jobs to babysit; One shared record, kept consistent. Load the existing set of Topics, Subscriptions, Messages, Rules / Filters into Dremio once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.
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 313 integrations available for Azure Service Bus and Dremio.
Popular · 7 of 313
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Azure Service Bus ⇄ MotherDuck -
Azure Service Bus ⇄ Databricks -
Azure Service Bus ⇄ AWS S3 -
Dremio ⇄ PagerDuty -
Dremio ⇄ Jira -
Dremio ⇄ Rabbitmq -
Dremio ⇄ Datadog
No integrations match .
