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Source channel @githubtrending · Post #14772 · Jun 1

#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

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以太坊区块链新闻| ETH 以太币圈热瓜

@ethereumglobalnews · Post #1454 · 12/01/2025, 06:57 AM

🪙 Vitalik: “You can just build on #L1” as fees stay cheap in 2025. #ETH 😎 Vitalik 表示: 由於 2025 年以太坊交易費持續保持低位,「直接在 L1 上構建」依然可行。今年以來 L1 需求增速溫和、區塊空間壓力未現顯著擁堵。 #Ethereum#DeFi#以太坊#市場趨勢 ——— ⚡️ 若費用長期維持低檔,L1 與 Rollup 的功能分工可能再度被市場重估 #Scaling ✅Chat: @Web3NewsInsight 🦂 👇Tip👇讚 或點擊進行💎資源搜索👇

以太坊区块链新闻| ETH 以太币圈热瓜

@ethereumglobalnews · Post #1618 · 12/26/2025, 04:57 AM

🪙 L1 Tokens 2025 Performance Castle Labs data shows most Layer 1 tokens ended 2025 in negative territory. Only BNB (+18.2%) and TRX (+9.8%) managed to stay in positive returns. • ETH:-15.3% • SOL:-35.9% • SUI / AVAX:跌幅均超 -67% • TON:全年回撤接近 -74% ⚡️ 結構性行情下L1 不再齊漲齊跌 #Ethereum#L1#CryptoMarkets #OnChain#BNB#以太坊 —————— 👇⭐️👇 🤣 🥲👇 資源搜索 🖲️👆

DeepSchool

@deep_school · Post #83 · 09/20/2022, 02:35 PM

Сегодня вторник, а значит в эфире рубрика “повторяем теорию”🤓 Вспомним про регуляризацию сетей, а именно про три популярных метода: L1, L2 и Dropout (ведь был популярен когда-то, надо отдать дань старичку). Статья в телеграфе 👉Регуляризуем правильно! #регуляризация#L1#L2#dropout