Azure Event Hubs Documentation

Key Features of Azure Event Hubs

Azure Event Hubs is a highly scalable data streaming platform and event ingestion service that can handle millions of events per second. It's designed for a variety of use cases, including real-time analytics, application logging, and fault-tolerant event processing.

High Throughput & Scalability

Event Hubs can ingest and process millions of events per second. Its elastic nature allows it to scale automatically based on your workload, ensuring your applications can handle bursts of traffic without interruption.

Durable Data Storage

Events sent to an Event Hub are durably stored for a configurable retention period (up to 7 days by default, extendable). This ensures that data is not lost, even if consumers are temporarily unavailable.

Consumer Groups

Event Hubs supports multiple, independent applications reading from the same event stream by using consumer groups. Each consumer group maintains its own offset within a partition, allowing for flexible consumption patterns.

Partitioning

Event Hubs partitions event streams to enable parallel processing. Data is ordered within a partition, and Event Hubs distributes events across partitions based on a partition key. This allows for parallel consumption and scalability.

Event Capture

Event Hubs Capture is a built-in feature that automatically and incrementally writes the data from Event Hubs to an Azure Blob Storage account or Azure Data Lake Storage Gen2 for long-term archival and batch processing with Azure Databricks, Azure HDInsight, or other big data analytics services.

Security and Compliance

Event Hubs offers robust security features, including Azure Active Directory integration, Shared Access Signatures (SAS), managed identities, and TLS encryption for data in transit. It also adheres to various compliance standards.

Integration with Azure Services

Event Hubs seamlessly integrates with a wide range of Azure services, such as Azure Functions, Azure Stream Analytics, Azure Logic Apps, and Azure Databricks, enabling end-to-end real-time data processing pipelines.

Use Cases

Key features enable Event Hubs for various scenarios:

  • Real-time Telemetry: Ingesting data from IoT devices, applications, and infrastructure.
  • Log Aggregation: Collecting logs from distributed systems for analysis and monitoring.
  • Event-Driven Architectures: Building microservices and applications that react to events in real-time.
  • Data Streaming Pipelines: Processing and transforming data streams for analytics, machine learning, and more.
  • Website Activity Tracking: Monitoring user interactions and website events.

Explore the overview to understand how these features contribute to a powerful data streaming solution.