TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

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

Results

1 similar post found

Search: #integrations

当前筛选 #integrations清除筛选
GitHub Trends

@githubtrending · Post #15384 · 01/02/2026, 12:00 PM

#other#awesome#chartjs#charts#integrations#plugins#resources Chart.js is a flexible JavaScript library for creating interactive charts with extensive customization options. You can use it with popular frameworks like React, Vue, and Angular through dedicated adapters, and extend its functionality with plugins for styling, features, and data handling. The library supports three major versions—v2 (April 2016), v3 (April 2021), and v4 (November 2022)—each with different plugin compatibility. This means you can choose the version that best fits your project needs and find compatible extensions for charts, animations, zooming, data labels, and more. Whether you need basic charts or advanced visualizations with custom interactions, Chart.js provides the tools to build professional data displays efficiently. https://github.com/chartjs/awesome