Time-Based Anti-Patterns for Caching Time-Series Data

In high throughput, read-heavy systems like ScyllaDB, effective caching is crucial for performance, as it significantly speeds up data retrieval compared to accessing storage. The article explores the scenarios and challenges of caching time-series data, particularly in IoT applications, by examining how ScyllaDB handles queries for time ranges. It highlights the differences between querying with a fixed time range versus using an open-ended range, explaining that while both methods appear similar, they have distinct impacts on the cache's efficiency. Using an open-ended range can optimize performance by allowing the cache to stay updated with new data, thus serving future queries entirely from the cache without requiring storage access. The article underscores the importance of understanding cache operations to avoid anti-patterns and ensure optimal performance in systems reliant on time-series data.