6 مستودعات
Settings and parameters defining how data is indexed, mapped, and stored for optimized retrieval.
Explore 6 awesome GitHub repositories matching data & databases · Data Storage Configurations. Refine with filters or upvote what's useful.
Elasticsearch is a distributed search engine and document store designed for the high-performance indexing and retrieval of massive volumes of unstructured data. It functions as a centralized analytics platform, providing a schema-flexible architecture that organizes information into searchable indices while maintaining global cluster state through a distributed consensus mechanism. The platform distinguishes itself through its integrated approach to observability, security, and advanced analytics. It combines full-text, vector, and hybrid search capabilities with machine learning-driven insi
Configures advanced data mappings and text analysis settings to optimize unstructured content for search.
This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d
Enables configuration of storage locations for synchronized data files.
MyBatis is a Java persistence framework that functions as a database query mapper and object-relational mapping tool. It decouples SQL statements from application code, allowing developers to manage database interactions by mapping Java objects to relational database records. The framework provides a centralized approach to SQL query management, enabling the use of either XML configuration files or annotations to define persistence logic. It automates the transformation of database result sets into structured objects, which eliminates the need for manual data conversion and reduces repetitive
Allows defining persistence logic and mappings through configuration files or annotations.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Defines custom storage settings, eviction policies, and backup counts for named data structures to ensure consistent performance.
هذا المشروع عبارة عن مجموعة من نماذج التنفيذ والمشاريع التجريبية التي تغطي الرؤية الحاسوبية، وأتمتة DevOps، والأنظمة الموزعة، والخدمات المصغرة (Microservices) المعتمدة على Java. يوفر المشروع مكتبة مرجعية برمجية وأمثلة عملية لبناء تطبيقات جانب الخادم (Server-side)، وحاويات الخدمات، وإدارة المجموعات (Clusters). يحتوي المستودع على مجموعة أدوات شاملة لأتمتة DevOps، بما في ذلك سكربتات وكتيبات تشغيل (Playbooks) لخطوط أنابيب CI/CD وتثبيت المجموعات المؤتمت. كما يتضمن مشروعاً تجريبياً للرؤية الحاسوبية لاكتشاف الكائنات في الصور وتحليل الوجوه، بالإضافة إلى أدلة مفصلة وملفات إعدادات لعمليات الحاويات باستخدام Docker والنشر عبر Kubernetes. يغطي المشروع نطاقاً واسعاً من قدرات الأنظمة الموزعة، بما في ذلك تنفيذ gRPC وRESTful API، وطوابير الرسائل، وبث البيانات. كما يتناول مراقبة البنية التحتية من خلال التتبع الموزع (Distributed Tracing) ومراقبة أداء النظام، إلى جانب معالجة البيانات الضخمة وتحسين تخزين البيانات. تتضمن قاعدة الكود أمثلة تنفيذية للغتي Java وGo، مع توفير الكود المصدري للتجميع الثنائي الأصلي (Native binary) وبناء الحاويات متعدد المراحل.
Provides operational examples for scaling data stores using master-slave configurations, replica sets, and indexing.
This project is a self-hosted application performance monitoring tool designed for Ruby on Rails environments. It functions as a diagnostic platform that tracks request response times, database query efficiency, and background job performance to help identify bottlenecks within web application infrastructure. The tool distinguishes itself by integrating directly into the framework to provide real-time performance insights and developer-focused utilities, such as direct navigation from error reports to the corresponding lines in a code editor. It supports complex analysis by correlating perfor
Allows configuration of storage destinations and namespaces for performance data.