Eng — Keydb

: It supports complex data structures beyond simple key-value pairs, including Sorted Sets Secondary Indexing

: It supports different levels of on-disk persistence, including RDB and AOF, to ensure data durability. 3. Performance Metrics In benchmarking tests (often conducted using the keydb eng

🛠️ Executing complex queries on large datasets to serve targeted advertisements in real-time. : It supports complex data structures beyond simple

: Uses a specialized snapshotting mechanism that reduces memory overhead and prevents latency spikes during data persistence. : Uses a specialized snapshotting mechanism that reduces

Large-scale datasets (hundreds of gigabytes to terabytes) that exceed cost-effective RAM limits, persistent NoSQL databases, and workloads with highly stratified "hot" and "cold" data patterns. Architectural Feature Comparison Default In-Memory Engine FLASH (RocksDB) Engine Primary Media System RAM SSD / NVMe (+ RAM Cache) Capacity Limit Strictly limited by physical RAM Limited by available disk space Cost per GB Write Model In-Memory with optional async disk logging LSM-Tree disk compaction Throughput Maximum possible (Millions of OPS) High (dependent on disk I/O capabilities) Data Eviction LRU/LFU policy when RAM is full Handled natively via disk tiering How to Configure the KeyDB Storage Engine