Search Results for "ram disk"

A high-performance NoSQL database based on bitcask, supports string, list, hash, set, and sorted set. rosedb is a fast, stable, and embedded NoSQL database based on bitcask, that supports a variety of data structures such as string, list, hash, set, and sorted set. Easy to embed into your own Go application. High performance, suitable for both read and write-intensive workloads. Values are not limited by RAM. It is similar to Redis but store values on disk. RoseDB is based on bitcask.

RocksDB uses a log structured database engine, written entirely in C++, for maximum performance. Keys and values are just arbitrarily-sized byte streams. RocksDB is optimized for fast, low latency storage such as flash drives and high-speed disk drives. RocksDB exploits the full potential of high read/write rates offered by flash or RAM. RocksDB is adaptable to different workloads. From database storage engines such as MyRocks to application data caching to embedded workloads, RocksDB can be used for a variety of data needs. RocksDB provides basic operations such as opening and closing a database, reading and writing to more advanced operations such as merging and compaction filters.

...It combines the speed of flat-file storage with enterprise features: schema-driven multi-dimensional indexing, ACID-compliant transactions with Strict Two-Phase Locking (Strict 2PL), columnar faceted navigation, multilingual locale processing, and native RAM-disk caching.

About MayWeb is a lightweight, beautifully designed local development environment built with ❤️. It lets you control Apache, MySQL, Redis, PHP versions, and more-all from a fast, modern UI. Ideal for developers who want performance, simplicity, and style in one powerful tool.

AvanceDB is a high-performance, in-memory database designed to accelerate SQL-based applications. It uses advanced caching techniques to reduce database latency and improve query execution speed, making it ideal for real-time analytics and transactional workloads.

This is an implementation of the java DOM specification that keeps all its "parsed-node" data in disk files instead of RAM. This means you can create really big DOM trees an not use all your RAM.