GitHub Trends

#java#cache#caffine#data#draft#fetch#graphql#immer#immutable#immutable_collections#immutable_datastructures#java#jdbc#kotlin#orm#orm_framework#orm_library#orms#redis#redis_cache Jimmer is a powerful and advanced ORM (Object-Relational Mapping) framework for Java and Kotlin that lets you easily read and write complex data structures without needing to predefine their shapes. It supports dynamic multi-table queries, automatic SQL optimization, and efficient saving of incomplete or nested objects. Jimmer also generates type-safe DTOs (Data Transfer Objects) for complex queries and updates, avoids common problems like "N+1" queries, and offers strong caching and GraphQL support. This means you can build complex business logic faster and with less hassle, improving both development speed and code quality. It works well with modern IDEs and supports both Java and Kotlin seamlessly. https://github.com/babyfish-ct/jimmer

#python#python#redis#redis_client#redis_cluster#redis_py Redis-py lets you connect your Python programs to Redis, a fast in-memory database, making it easy to store and retrieve data quickly. You can install it with a simple command, and it works with the latest Redis versions. It supports advanced features like connection pools, pipelines for faster operations, and pub/sub for real-time messaging. Using Redis with Python helps your applications run faster, handle more users, and process data in real time, all while reducing the load on your main database[1][3][5]. https://github.com/redis/redis-py

#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

#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai

#javascript#approval_process#cms#crm#ehr#erp#hr#layui#mysql#oa#privileges#redis#skyeye#springboot#springboot2#springcloud_vue#websocket This platform uses Springboot, Layui, UNI-APP, and Ant Design Vue to create a low-code system for intelligent manufacturing. It includes over 30 application modules and more than 50 electronic workflows, covering CRM, ERP, MES, and more. This system streamlines business processes from customer relations to production and after-sales service, improving efficiency and data transparency. It also manages employee operations, providing a comprehensive solution for businesses. The benefits include faster development, reduced redundancy, and enhanced data management, making it ideal for companies seeking digital transformation. https://github.com/dromara/skyeye