TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15244 · Oct 24

#python#airtable#airtable_alternative#airtable_replacement#application_builder#automations#dashboards#database#low_code#no_code#no_code_database#no_code_platform#online_database#postgresql#restful_api#self_hosted#spreadsheet Baserow is a powerful, open-source tool that lets you build databases and applications without coding. It offers full control over your data and environment, allowing self-hosting and customization. Unlike Airtable, Baserow doesn't limit your data storage or API calls, making it ideal for large projects. It combines the ease of a spreadsheet with advanced data management features, including dashboards and automation tools. This gives users complete ownership of their data and avoids vendor lock-in, making it a great choice for businesses needing flexibility and scalability. https://github.com/baserow/baserow

Results

2 similar posts found

Search: #valkey

当前筛选 #valkey清除筛选
科技&趣闻&杂记

@kejiqu · Post #3325 · 05/02/2025, 01:18 AM

Redis 8 再次切换到开源许可证 AGPLv3 Redis 于 2024 年 3 月将其 7.4 版本及以上版本的许可证从 3-clause BSD 变更为 RSALv2 和 SSPLv1 双许可证,商业使用需授权,此举使其不再是 FOSS。开源社区对此做出反应,创建了分支,其中 Valkey 得到了 Linux 基金会、Google、AWS 和甲骨文的支持。一年后,Redis 公司发布 8.0 版本,重新采用开源许可证,新增 AGPLv3 作为选项。 AGPLv3 完全兼容 GPLv3,继承了它的自由软件精神:你可以自由使用、修改和分发软件,但必须开源你修改后的源代码。Solidot | Redis |GitHub 🏷#Redis#许可证#开源#Valkey 📢频道👥群组📝投稿

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