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Cloud Data Engineering
25 minintermediate

Azure Event Hubs for Streaming Ingestion

Azure Event Hubs is Azure's fully managed real-time event streaming service — the Azure equivalent of Amazon Kinesis Data Streams or Apache Kafka. It ingests millions of events per second, buffers them for a configurable retention period, and enables multiple consumer groups to process the same event stream independently. Event Hubs is natively compatible with the Apache Kafka protocol — existing Kafka producers and consumers connect by updating only the broker endpoint, enabling migration from self-managed Kafka to Azure-managed Event Hubs without any code changes.

An Event Hub is the Azure equivalent of a Kafka topic — a named stream of events organised in Event Hubs Namespaces (the capacity and billing unit). Each Event Hub is divided into partitions — the parallelism unit, equivalent to Kafka partitions and Kinesis shards. Partition count is fixed at creation and cannot be changed without recreating the Event Hub. Event Hubs Standard supports up to 32 partitions and 1-day retention. Premium and Dedicated tiers support higher partition counts and retention up to 90 days.

Analogy🏏Cricket
🏏 Think of it like cricket: This exercise is the IPL official statistics team building their daily automated processing pipeline — the complete workflow that takes raw ball-by-ball records from every ground and produces the certified statistics published on the official website by midnight. Stage 1 is the data catalogue check: verify that the incoming scorecards match the expected format before any processing begins. Stage 2 is the statistics calculation: joins with match metadata, derivation of over-level stats, economy rate computation. Stage 3 is the official record update: load the new statistics into the production database using the certified upsert protocol — delete the old version of today's record and insert the freshly computed one — so no match ever has two records in the official database.
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