Two-way sync
Changes in Apache Pinot or Azure Service Bus instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Pinot and Azure Service Bus in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Apache Pinot is the central store where teams keep Tenants, Tables, Schemas, Segments 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 Apache Pinot, and the curated rows in Apache Pinot 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 Tenants, Tables, Schemas, Segments in Apache Pinot 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.
Load the existing set of Queues, Topics, Subscriptions, Messages into Apache Pinot once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.
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.
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.
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.
| Apache Pinot objects | Azure Service Bus objects | How this pairing syncs | |
|---|---|---|---|
| Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | 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 is specific to Apache Pinot and Dead-letter queue to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | 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. | Tenants is specific to Apache Pinot and Scheduled / deferred messages to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | 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. | Tables is specific to Apache Pinot and Queues to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | 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 is specific to Apache Pinot and Topics to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | 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. | Segments is specific to Apache Pinot and Subscriptions to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | 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. | Real-time Tables is specific to Apache Pinot and Messages to Azure Service Bus — 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 Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.
DeliveryEach detected change is written to Azure Service Bus through its API, with automatic retries and rate-limit backoff.
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 Apache Pinot as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Azure Service Bus connection.
Changes in Apache Pinot or Azure Service Bus instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Pinot or Azure Service Bus data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Pinot or Azure Service Bus record.
Track your Apache Pinot ⇄ Azure Service Bus sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Pinot and Azure Service Bus.
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 Apache Pinot and Azure Service Bus 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 Apache Pinot and Azure Service Bus 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 Apache Pinot and Azure Service Bus: authenticate both systems, choose the objects to sync (such as Apache Pinot's Indexes and Tenants), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Apache Pinot and Azure Service Bus. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Pinot: Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes. 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. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Pinot side: Tenants, Tables, Schemas, Segments, plus custom fields where Apache Pinot exposes them. On the Azure Service Bus side: Queues, Topics, Subscriptions, Messages. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Apache Pinot and Azure Service Bus: Backfill history, then stay live; No batch jobs to babysit; One shared record, kept consistent. Load the existing set of Queues, Topics, Subscriptions, Messages into Apache Pinot once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.
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 Apache Pinot and Azure Service Bus.