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Lähdekanava @mariinavodesign · Post #708 · 12.6.

Эффект Liquid Glassв Figma — как в новом обновлении от Apple 🪄 В комментариях — инструкция, как собрать эффект вручную А для тех, кто на платформе Ready? Set. Create!, доступен шаблон этого эффекта в разделе Шаблоны Figma — его можно дублировать в свой проект и сразу применить 🫰🏼 #figma@mariinavodesign

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@githubtrending · Post #14772 · 01.06.2025 klo 00.00

#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4]. https://github.com/dragonflydb/dragonfly