Why Your Database Needs a Time-Series Partitioning Strategy

Episode 59 of Database Tech with Fexingo tackles the growing challenge of time-series data in modern databases. Lucas and Luna explore why most default partitioning strategies fail for high-ingestion rate workloads, using a detailed example of a real-time IoT sensor system processing 10,000 writes per second. They discuss the hidden cost of partition splits, the importance of pre-creating partitions on a rolling window, and how to avoid the 'hot partition' problem that leads to I/O bottlenecks and query slowdowns. Practical advice on choosing partition granularity for different data retention policies, plus a look at how PostgreSQL and ClickHouse handle time-series partitioning differently. If you're managing logs, metrics, or any append-heavy workload, this episode gives you a concrete strategy to keep query performance predictable and avoid midnight outages when the partition you need doesn't exist yet. #Database #TimeSeriesData #Partitioning #PostgreSQL #ClickHouse #IoT #DataEngineering #QueryPerformance #DataStorage #TechPodcast #FexingoBusiness #BusinessPodcast #SQL #NoSQL #Scalability #DatabaseDesign #PartitionPruning #RealTimeData Keep every episode free: buymeacoffee.com/fexingo