Two-way sync
Changes in Amazon RDS or Azure Service Bus instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon RDS 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.
Amazon RDS 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 Tables, Views, Columns, Primary and Unique Keys in Amazon RDS with Sessions, Dead-letter queue, Scheduled / deferred messages, Queues 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.
Directory and identity records in Azure Service Bus stay matched to the users or owners table in Amazon RDS, so provisioning and de-provisioning flow from one source.
A new or changed row in Amazon RDS creates or updates the matching record in Azure Service Bus, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
Records and events from Azure Service Bus arrive in Amazon RDS as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
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.
| Amazon RDS objects | Azure Service Bus objects | How this pairing syncs | |
|---|---|---|---|
| Views Read-side projections exposed to outbound 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 is specific to Amazon RDS and Sessions to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Columns Field-level mapping targets, typed per the underlying engine. | 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. | Columns is specific to Amazon RDS and Dead-letter queue to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Match keys for idempotent upserts. | 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. | Primary and Unique Keys is specific to Amazon RDS and Scheduled / deferred messages to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Read Replicas Low-impact read endpoints often used as the source side of a sync. | 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. | Read Replicas is specific to Amazon RDS and Queues to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Stored Procedures Engine-specific logic that can react to synced rows. | 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. | Stored Procedures is specific to Amazon RDS and Topics to Azure Service Bus — each maps to any object or custom field on the other side. | |
| Databases Engine-level databases on the instance that scope a sync's reads and writes. | 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. | Databases is specific to Amazon RDS and Subscriptions 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.
DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.
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 Amazon RDS as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon RDS–Azure Service Bus connection.
Changes in Amazon RDS or Azure Service Bus instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon RDS 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 Amazon RDS or Azure Service Bus record.
Track your Amazon RDS ⇄ Azure Service Bus sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon RDS 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 Amazon RDS 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 Amazon RDS 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 Amazon RDS and Azure Service Bus: authenticate both systems, choose the objects to sync (such as Amazon RDS's Views and Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Amazon RDS and Azure Service Bus: Where Azure Service Bus manages users or groups: keep identity aligned; Turn rows into the records your tools track; Land tool activity as queryable rows. Directory and identity records in Azure Service Bus stay matched to the users or owners table in Amazon RDS, so provisioning and de-provisioning flow from one source.
Amazon RDS: SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle). Authentication: Database credentials over SSL/TLS, or IAM database authentication on supported engines. 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. Stacksync manages authentication, retries, and rate limits on both sides.
Amazon RDS: CDC prerequisites such as binlog row format or logical replication are configured through RDS parameter groups, since superuser access is not provided. Azure Service Bus: Messages that exceed the max delivery count (default 10) or their time-to-live are moved automatically to the entity's dead-letter sub-queue rather than dropped, where they can be inspected and reprocessed. Stacksync's field mapping accounts for these differences between Amazon RDS and Azure Service Bus 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 Amazon RDS and Azure Service Bus records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon RDS and Azure Service Bus connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon RDS–Azure Service Bus 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 333 integrations available for Amazon RDS and Azure Service Bus.