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Chaîne source @OnePlusGuide · Post #3085 · 23 mars

🔻SEGUI LA PRESENTAZIONE DEI ONEPLUS 9 CON NOI🔻 #OP#OP9PRO#OP9R#LIVE Siamo felici di annunciarvi che, come per OnePlus 8 ed 8T commenteremo Live presentazione di OnePlus 9 oggi dalle ore 14:30. Quest'anno abbiamo deciso di utilizzare ben 2 piattaforme per lo streaming, infatti saremo Live sia su YouTube che su Twitch. 📝 Per ricordarvi dell'evento vi consigliamo attivare la campanella sulla vostra piattaforma preferita tramite i link sottostanti. Vi aspettiamo numerosissimi! 🟣LIVE TWITCH (principale) 🔴LIVE YOUTUBE 📝 Dalle 14:45 gruppi verranno chiusi per spostare le discussioni in live — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity

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3 posts similaires trouvés

Recherche : #memcached

当前筛选 #memcached清除筛选
djangoproject

@djangoproject · Post #411 · 13/08/2017 12:08

http://sendapatch.se/projects/pylibmc/ #pylibmc is a client in Python for #memcached. It is a wrapper around TangentOrg‘s libmemcached library. The interface is intentionally made as close to python-memcached as possible, so that applications can drop-in replace it. pylibmc leverages among other things configurable behaviors, data pickling, data compression, battle-tested GIL retention, consistent distribution, and the binary memcached protocol.

djangoproject

@djangoproject · Post #410 · 13/08/2017 11:53

https://pypi.python.org/pypi/python-memcached This software is a 100% Python interface to the #memcached#memory#cache daemon. It is the #client side software which allows storing values in one or more, possibly remote, memcached servers. Search google for memcached for more information.

GitHub Trends

@githubtrending · Post #14772 · 01/06/2025 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