In-Memory

In Memory Databases: Speed at Your Fingertips In memory databases store data in RAM rather than on disk. This design bypasses much of the slow disk I/O, so reads and writes happen in microseconds. The speed boost makes these systems a good fit for tasks that need immediate results. Yet RAM is volatile and memory capacity is limited, so you should plan for durability and growth. Common use cases Real-time analytics and dashboards Session stores and fast caching Leaderboards and live gaming state Price ticks and monitoring data How they work Most in-memory databases keep hot data in memory and offer fast data structures for quick access. They can run with different interfaces, from simple key-value styles to SQL-like queries. Some systems run mostly in memory but periodically write changes to disk, forming a hybrid model that balances speed with durability. ...

Persistent Data and Caching Strategies for High Performance Performance often comes from reading data fast. A well-used cache can cut latency and reduce load on storage. But stale data or lost writes can hurt trust. The goal is to keep data readily available while still writing to a durable store. In a modern app, caching happens at multiple layers: in-process memory, a distributed cache like Redis or Memcached, and a CDN for static content. Each layer offers different speed and persistence characteristics. ...