ClickHouse Integration with Azure Synapse guide

Azure Synapse, a data platform that efficiently orchestrates data transformations using Spark pools, manages data lake storage with ADLS Gen2, and provides SQL analytics capabilities, can face performance challenges when deployed for real-time analytics serving. Although Synapse is adept at orchestrating complex ETL workflows and managing data lake governance, it struggles with high concurrency workloads and sub-second query performance required for customer-facing dashboards. The integration with ClickHouse, known for low-latency query serving, offers a solution through various patterns, including using Synapse Spark with ClickHouse connectors or ADLS Gen2 as a staging layer. While these integrations provide specific benefits, they require significant engineering efforts, such as connector configuration, network setup, and schema mapping. Alternatively, platforms like Tinybird offer managed solutions with built-in data pipeline capabilities that simplify integration complexities, focusing on real-time analytics and SQL transformations without the need for Spark jobs, thus catering to teams prioritizing operational simplicity and sub-100ms serving for dashboards and APIs.

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