Search Results for "data structures"

Redis is an open-source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions, and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster. ...

...Valkey natively supports a rich collection of datatypes, including strings, numbers, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, and more. You can operate on data structures in-place with an expressive collection of commands. Valkey also supports native extensibility with built-in scripting support for Lua and supports module plugins to create new commands, data types, and more.

AmberDB is a high-performance, flat-file NoSQL database engine for Perl built on top of Berkeley DB (DB_File). 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.

...Redis is an open-source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions, etc.

...If you follow the tests/examples, you too can store dictionaries, trees, lists or whatever you can think of in disk-based memory, just an open() and mmap() away. Meta-treedb comes with an AVL tree, doubly-linked-list and variable-entry-sized-array implementations for you to use in your data structures. So, what distinguishes meta-treedb from treedb? * "class" interfaces for treedb collections These are vtables (virtual function tables) that implement the interface. * faster compiles - only the "class" interfaces are visible to client code This is at the expense of a small performance hit. * the ability to use implementations that were developed after client code was compiled.

ARMR provides a foundation for creating an efficient in-memory database. Its unique list processing structures simplify programming logic and allow the developer to rapidly sort, group, and select data. Give your app a hypercard like capability.

NWrapper was built to be a quick wrapper for storing and executing multiple NMap commands (using SQLite), but it can do a lot more. Also, it was a way for me to start learning C (hence the lack of data structures or anything fancy).

Fast data loading from DBF ( dbf , xBASE , Clipper ) files of arbitrary structures into RBDMS Oracle. Excellent for mass files loading. May be the fastest tool possible. Automatic tables creation from dbf files. No problems with reserved words.