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How Sony LIV uses ClickHouse Cloud to deliver live streaming analytics at billion-row scale
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Sony LIV consolidated its fragmented batch, Elasticsearch, and BigQuery workloads onto ClickHouse Cloud, enabling sub-second query latency on billions of daily streaming events.
Engineers gain a unified data platform that reduces query latency from tens of seconds to under a second during live events. The consolidation eliminates the need to stitch together data from multiple systems, simplifying real-time dashboards for QoS and QoE monitoring. Cost-efficient storage and high ingestion throughput help manage billions of telemetry events per day without the previous cost growth.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
Sony LIV moved from a fragmented stack of batch pipelines, Elasticsearch, and BigQuery to a single ClickHouse Cloud platform.
Query latency dropped from tens of seconds or minutes to less than a second for billions of daily streaming events.
The platform provides high ingestion throughput, cost-efficient storage, and near real-time processing for operational dashboards during live traffic spikes.
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Before adopting ClickHouse Cloud, Sony LIV relied on a mix of batch pipelines, Elasticsearch, and BigQuery for its analytics workloads.
Their systems were optimized for batch processing rather than ultra-low latency streaming.
During live sports events, operational teams needed visibility within seconds, not minutes, but existing pipelines could not deliver that speed.
Query performance degraded as telemetry volumes grew into billions of events per day, making ad-hoc analyses slow and expensive.
Fragmentation forced engineers to stitch together data from multiple sources, delaying insights.
Sony LIV evaluated several analytics platforms and selected ClickHouse Cloud because of its architecture and performance for large-scale analytical workloads.
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