Migrating Data to Azure Synapse with Confluent’s Fully Managed Connector to Unlock Real-Time Advanced Analytics

Confluent’s integration with Azure Synapse Analytics is presented as a way to move and process real-time data from on-premises, open-source, hybrid-cloud, and other distributed systems for analytics, reporting, applications, and services. Using Confluent Cloud’s managed Azure Synapse Analytics Sink Connector, Kafka topic data can be loaded into Synapse dedicated SQL pools, with optional automatic table and schema creation, while Synapse Spark Structured Streaming can directly consume Kafka data for real-time processing and storage in destinations such as Azure Data Lake Storage. The setup requires Azure and Confluent accounts, existing Kafka topic data, appropriate Synapse permissions and firewall access, and compatible Spark packages for Kafka connectivity. Key limitations include Synapse’s lack of primary-key support for connector-driven updates, upserts, and deletes, as well as schema-evolution behavior that leaves existing records null for newly added columns with defaults. The integration aims to reduce the complexity and cost of hybrid and multicloud data pipelines while supporting real-time use cases such as fraud detection, monitoring, risk analysis, IoT, and event-level analytics.

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