TGTGInsighttelegram intelligenceLIVE / telegram public index
← YxVM‘s NOTICE

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @yxvmcom · Post #21 · Nov 10

#Features 我们打开了一项新的功能,此功能目前处于测试阶段,我们将此功能命名为 AnyLAN,你可以使用它快速的建立内网,并且不消耗你的公网流量。 目前此功能分为2个场景: 1. 同节点内网 2. 不同节点内网(2个节点或以上) 我们这里提供一份简易的教程供大家参考:https://yxvm.com/index.php?rp=/knowledgebase/2/How-to-use-AnyLAN.html 需要开启此功能,你必须购买相应产品(目前免费) LAN (必须同节点持有2个以上VPS才可购买): https://yxvm.com/cart.php?pid=44&promocode=DLCH0P1DN7 AnyLAN(必须俩个或以上节点持有VPS才可购买):https://yxvm.com/cart.php?pid=45&promocode=83YHPHA6QG *LAN 限速500Mbps AnyLAN限速100Mbps

Hashtags

Results

3 similar posts found

Search: #memcached

当前筛选 #memcached清除筛选
djangoproject

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

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 · 08/13/2017, 11:53 AM

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 · 06/01/2025, 12:00 AM

#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