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Azure provides several services for delivering events and messages throughout a solution. Each service targets different scenarios, from reactive event routing to high-throughput streaming to enterprise-grade transactional messaging.
This article compares the following services:
Choose a candidate service
This section helps you select the most likely services for your needs.
Use the following table to quickly narrow down which service fits your scenario:
| Criterion | Event Grid | Event Hubs | Service Bus |
|---|---|---|---|
| Primary purpose | Reactive event routing | Big data streaming and ingestion | Enterprise transactional messaging |
| Data model | Events (discrete notifications) | Event streams (time-ordered series) | Messages (high-value payloads) |
| Delivery guarantee | At least once | At least once | At least once (optional ordered, exactly once with sessions) |
| When to use | React to status changes, serverless architectures | Telemetry, distributed data streaming, real-time analytics | Order processing, financial transactions, workflows |
The result of this section is a starting point for consideration. Use the following sections to perform a detailed evaluation of the services.
Events vs. messages in Azure messaging services
There's an important distinction between Azure services that deliver an event and services that deliver a message.
Event: A lightweight notification of a condition or state change. The publisher has no expectation about how the event is handled. Events can be discrete (reporting a state change that's actionable) or part of a time-ordered series (reporting a condition that's analyzable). Discrete events are ideal for serverless solutions that need to scale.
Message: Raw data produced by a service to be consumed or stored elsewhere. The message contains the data that triggered the message pipeline. A contract exists between publisher and consumer. For example, the publisher sends a message with raw data, and expects the consumer to create a file from that data and send a response when the work is done.
Scalability and throughput
The following table compares how Azure Event Grid, Azure Event Hubs, and Azure Service Bus handle scalability and throughput.
| Criterion | Event Grid | Event Hubs | Service Bus |
|---|---|---|---|
| Throughput | Dynamically scalable, serverless | Millions of events per second | Reliable asynchronous delivery |
| Latency model | Near-real-time event delivery | Low latency streaming | Brokered with optional long polling |
| Scaling model | Automatic (serverless) | Throughput units / processing units | Messaging units (Premium) |
Messaging features
The following table compares the messaging features of Azure Event Grid, Azure Event Hubs, and Azure Service Bus.
| Criterion | Event Grid | Event Hubs | Service Bus |
|---|---|---|---|
| Protocol | MQTT, HTTP | AMQP, Kafka, HTTP | AMQP, HTTP |
| Pub/Sub | Yes (publish-subscribe) | Yes (consumer groups) | Yes (topics and subscriptions) |
| Ordering | No guarantee | Per partition | FIFO (sessions) |
| Transactions | No | No | Yes |
| Duplicate detection | No | No | Yes |
| Dead-lettering | Yes | No | Yes |
| Batching | Yes | Yes (event batches) | Yes (sessions) |
| Capture / replay | No | Yes (Event Hubs Capture) | No |
Integration and deployment
The following table compares integration and deployment options for Azure Event Grid, Azure Event Hubs, and Azure Service Bus.
| Criterion | Event Grid | Event Hubs | Service Bus |
|---|---|---|---|
| Azure service integration | Deep integration with Azure services and third-party services | Stream-processing infrastructures and analytics services | Enterprise applications, hybrid cloud, on-premises connectivity |
| Editions | Azure Event Grid (PaaS), Event Grid on Kubernetes with Azure Arc | Standard, Premium, Dedicated | Basic, Standard, Premium |
Use Event Grid, Event Hubs, and Service Bus together
In some cases, you use the services side by side to fulfill distinct roles. For example, an e-commerce site can use Service Bus to process orders, Event Hubs to capture site telemetry, and Event Grid to respond to events like an item being shipped.
In other cases, you link them together to form an event and data pipeline. You use Event Grid to respond to events in the other services. For an example of using Event Grid with Event Hubs to migrate data to Azure Synapse Analytics, see Stream big data into Azure Synapse Analytics. The following image shows the workflow for streaming the data.
