Eisan System Development replaced a QlikView-based analytics stack with ClickHouse Cloud to handle ID-POS retail data at scale. The old system struggled with growing data volumes, high memory consumption, and reliability failures. ClickHouse delivered stable query performance on lower-spec hardware, eliminated result failures, and reduced licensing costs. The team is now optimizing CPU-to-memory ratios, exploring autoscaling and scheduled shutdowns, and targeting 100 billion records as a future scale goal.
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The old system: costly and unreliable #ClickHouse to the rescue #The subtle art of server balance #What's next for Eisan and ClickHouse #Sort: