How #Netflix boosted #ApacheDruid performance: by implementing interval-aware…
How #Netflix boosted #ApacheDruid performance: by implementing interval-aware caching, they now serve 84% of analytics results from cache and have reduced query load by 33%.
The secret? Decomposing rolling window queries into reusable time segments. ✅ Reduces scan volume ✅ Improves P90 latency ✅ Optimizes real-time analytics
Details on #InfoQ: https://bit.ly/4uHG4DE
#SoftwareArchitecture #DistributedSystems #DataAnalytics #TimeSeriesData #Caching #BigData #DataEngineering
Netflix Serves 84% of Query Results from Cache with Interval-Aware Caching in Apache Druid
Netflix improves Apache Druid performance with interval aware caching, serving 84% of analytics results from cache and reducing query load by 33%. The system decomposes rolling window queries into reusable time segments, enabling partial cache reuse and recomputation only for recent data. At scale, it reduces scan volume, improves P90 latency, and optimizes real time analytics workloads.
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