InfoQ - Time Series Data

Article: Time-Series Storage: Design Choices That Shape Cost and Performance

Nirmesh Khandelwal — Tue, 12 May 2026 09:00:00 GMT

Every time-series database makes a set of storage design decisions: how to lay out rows, when to compress, what to partition on. These decisions determine cost and query performance more than the choice of database itself. This article works through those fundamentals from first principles, using widely available tools like PostgreSQL and Apache Parquet to make each trade-off measurable.

By Nirmesh Khandelwal

Netflix Serves 84% of Query Results from Cache with Interval-Aware Caching in Apache Druid

Leela Kumili — Mon, 11 May 2026 14:36:00 GMT

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.

By Leela Kumili