Azure Event Hubs Features

High Throughput and Scalability

Event Hubs is designed for massive data ingestion. It automatically scales to handle millions of events per second, making it suitable for large-scale telemetry, clickstream data, and IoT scenarios. You can adjust throughput units (TUs) or processing units (PUs) based on your needs.

Durable Event Storage

Events sent to Event Hubs are durably stored for a configurable retention period (typically 1 to 7 days, extendable). This allows consumers to process events at their own pace and enables replay of events if necessary. This is crucial for reliability and fault tolerance.

Consumer Groups

Event Hubs supports the concept of consumer groups. Each consumer group allows a separate application or service to independently read from the event stream without interfering with other consumers. This is essential for distributing the processing of event data among different microservices or analytical tools.

Partitioning

Event Hubs divides an event stream into one or more partitions. This partitioning allows for parallel processing of events, as each partition can be read concurrently by different consumer instances within a consumer group. The partitioning strategy can be based on a partition key or round-robin.

Geo-disaster Recovery and Geo-replication

Event Hubs offers built-in support for geo-disaster recovery and geo-replication. This ensures high availability and business continuity by replicating data across different Azure regions. You can configure active-passive or active-active disaster recovery scenarios.

Encryption at Rest and in Transit

Data security is paramount. Event Hubs encrypts all data automatically using service-managed keys or customer-managed keys (CMKs) when it's stored (at rest). Data is also encrypted in transit using TLS/SSL to protect it from unauthorized access during transmission.

Capture Feature

The Event Hubs Capture feature automatically captures the output of an Event Hub into an Azure Storage account (Blob storage or Data Lake Storage Gen2) on a configured interval or size. This enables batch analytics and archival of event data without writing custom code.

Captured data can be in Apache Avro format, which is efficient and schema-aware.

Schema Registry Integration

Event Hubs integrates with Azure Schema Registry, a centralized schema repository. This helps manage and enforce schemas for your event data, ensuring data consistency and compatibility between producers and consumers. This is particularly useful in complex microservice architectures.

Integration with Azure Services

Event Hubs seamlessly integrates with other Azure services, including:

• Azure Functions for event-driven processing.
• Azure Stream Analytics for real-time data transformation and analysis.
• Azure Databricks and Azure Synapse Analytics for big data analytics.
• Azure Logic Apps for workflow automation.
• Azure Data Explorer for interactive analytics.

Large Message Support

Event Hubs supports large messages (up to 1MB by default, with options for larger messages with specific configurations), allowing for richer event payloads.

Schema Evolution Management

With Schema Registry integration, you can manage schema evolution gracefully, allowing producers and consumers to adapt to changes in data structure over time without breaking the pipeline.