Awesome GitHub RepositoriesData Partitioning

هذا المشروع عبارة عن مورد تعليمي شامل ودليل دراسي يركز على بنية الأنظمة الموزعة وتصميم البنية التحتية للـ backend. يوفر منهجاً منظماً لإتقان مبادئ القابلية للتوسع، والموثوقية، والأداء المطلوبة لتصميم أنظمة برمجية معقدة. يتميز المستودع بتقديم نهج منهجي للتحضير للمقابلات التقنية، حيث يدمج أنماط التصميم، والمقايضات المعمارية، وأدوات التكرار المتباعد لمساعدة المستخدمين على الاحتفاظ بالمفاهيم المعقدة. ويؤكد على التحليل القائم على القيود، حيث يعلم المستخدمين كيفية تقييم المتطلبات المتنافسة مثل زمن الوصول (latency)، والاتساق، والتوافر عند صياغة التصاميم المعمارية. يغطي المحتوى طيفاً واسعاً من قدرات تصميم النظام، بما في ذلك استراتيجيات توسيع قواعد البيانات، وإدارة حركة المرور، وتحسين البنية التحتية. ويفصل تقنيات التوسع الأفقي، والتخزين المؤقت متعدد الطبقات، والتواصل غير المتزامن، واكتشاف الخدمات، مع توفير أطر عمل لإجراء تقديرات الموارد وتخطيط السعة. يتم تنظيم التوثيق كدليل دراسي، مما يوفر مساراً منهجياً عبر أساسيات هندسة الـ backend وتصميم الأنظمة واسعة النطاق.

Milvus is a specialized vector database engine designed for the indexing, management, and high-speed similarity retrieval of high-dimensional vector embeddings. It functions as a similarity search engine capable of identifying nearest neighbors within large-scale vector spaces, supporting the storage and retrieval of billions of data points while maintaining consistent performance. The system utilizes a distributed architecture that decouples storage, query, and coordination into independent services, allowing for horizontal scaling across clusters. It employs a global indexing mechanism that

This project is a comprehensive educational resource focused on the principles, patterns, and trade-offs required to design scalable, reliable, and high-performance distributed systems. It provides a structured curriculum that covers the fundamental architectural strategies necessary for building modern software infrastructure, ranging from high-level system decomposition to low-level networking and data management. The repository distinguishes itself by offering deep dives into complex architectural patterns, such as microservices-based decomposition, event-driven communication, and command-

Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors alongside structured metadata. It functions as a distributed search engine that manages large-scale data clusters, providing low-latency retrieval and complex filtering capabilities. The system is built to serve as a specialized middleware layer, connecting machine learning pipelines and AI agents to persistent storage for intelligent information retrieval and recommendation tasks. The platform distinguishes itself through advanced retrieval techniques, including support for h

RocksDB is a high-performance, embeddable persistent key-value library and storage engine based on Log-Structured Merge-trees. It is designed to provide durable storage for large-scale datasets, integrating directly into applications to manage data on flash and RAM-based hardware. The engine is distinguished by its focus on minimizing read and write amplification through multi-threaded compaction and custom memory allocators. It features specialized optimizations for flash storage, including support for zoned block devices, and provides the ability to extend store behavior via external plugin

This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure. The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, whi

This project is a comprehensive educational resource and technical documentation suite for learning and developing deep learning models. It serves as an open-source textbook, implementation manual, and framework tutorial designed to guide users through the mathematical foundations and practical application of neural networks. The resource provides detailed instructional content on building various model architectures, including convolutional and recurrent neural networks. It includes a dedicated distributed training guide and a learning path that covers the fundamentals of tensors, automatic

Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative modeling and version-controlled code. It functions as a workflow engine that treats data assets as first-class primitives, allowing teams to define, schedule, and monitor complex pipelines while maintaining clear visibility into lineage, dependencies, and data quality. The platform distinguishes itself by using a code-as-configuration framework that enables standard software engineering practices, such as unit testing and local mocking, to be applied directly to data workflows.

Druid is a distributed columnar store and online analytical processing database designed for real-time analytics. It functions as a SQL analytics platform and a streaming data ingestion engine, allowing for the analysis of large datasets with low latency to support interactive dashboards and high-concurrency operational workloads. The system integrates a streaming data ingestion engine that loads information via batch or streaming processes to enable immediate analysis of arriving data. It provides high-performance analytical processing to execute slice-and-dice queries on massive data volume

Dask هو إطار عمل للحوسبة المتوازية وجدول مهام موزع مصمم لتوسيع نطاق سير عمل علوم البيانات في Python من أجهزة فردية إلى مجموعات (clusters) كبيرة. يعمل كمدير موارد للمجموعة يقوم بتنسيق المنطق الحسابي من خلال تمثيل المهام وتبعياتها كرسوم بيانية موجهة غير دورية. تسمح هذه البنية للنظام بأتمتة توزيع أعباء العمل عبر الأجهزة المتاحة مع إدارة متطلبات التنفيذ المعقدة. يتميز المشروع بمحرك تقييم كسول يؤجل عمليات البيانات حتى يتم طلبها صراحة، مما يتيح تحسين الرسم البياني العالمي وتخصيص الموارد بكفاءة. يتضمن خاصية تسريب البيانات الواعية بالذاكرة لمنع تعطل النظام عند معالجة مجموعات البيانات التي تتجاوز الذاكرة المتاحة، ويستخدم دمج الرسم البياني للمهام لدمج تسلسلات العمليات في خطوات تنفيذ واحدة، مما يقلل من عبء الجدولة والاتصال بين العقد. توفر المنصة سطح قدرات شاملاً لتحليلات البيانات واسعة النطاق، بما في ذلك دعم التعلم الآلي الموزع، وتكامل الحوسبة عالية الأداء، ومعالجة البيانات المتوازية. توفر أدوات واسعة النطاق لإدارة دورة حياة المجموعة، وتوصيف الأداء، والمراقبة في الوقت الفعلي لتنفيذ المهام. يمكن للمستخدمين نشر هذه البيئات عبر بنية تحتية متنوعة، بما في ذلك الأجهزة المحلية، ومزودي السحابة، والأنظمة الحاوية، ومجموعات الحوسبة عالية الأداء.

Electric is a Postgres data synchronization engine and replication proxy designed to enable local-first software. It replicates data from Postgres databases to client-side stores in real time using logical replication, allowing applications to maintain a local embedded database for offline access and low-latency updates. The system distinguishes itself by using shapes to filter and authorize specific subsets of database rows and columns before streaming them to clients or edge workers. It further supports multi-user collaboration by integrating a conflict-free replicated data type framework t

Cassandra is a distributed NoSQL database and wide-column store designed for high availability and linear scalability. It functions as a fault-tolerant distributed system that utilizes an LSM-tree storage engine to optimize write throughput and manage massive datasets. The system is a CQL-compliant database, using a structured query language to manage and retrieve tabular data stored across multiple nodes. It organizes information into rows and columns based on a flexible schema and primary keys. The project provides capabilities for horizontal database scaling, distributed data partitioning

pprof is a tool for visualizing and analyzing performance profiling data. It converts sampled call stacks into a directed graph rendered as an SVG, enabling visual identification of execution hotspots. The tool also parses Linux perf.data files, converting them into an internal profile representation for further analysis. Beyond visualization, pprof provides a command-line REPL for interactive exploration of profiling data, allowing users to filter, refine, and query performance information on the fly. It generates sorted text reports that highlight the most resource-intensive call stacks, an

This project is an open-source software development kit and framework for implementing the Matter smart home standard. It provides a universal IPv6-based application layer and a cluster-based data model to ensure interoperability between diverse smart home devices and controllers. The system is distinguished by its multi-transport network abstraction, which maps Bluetooth LE, Thread, and Wi-Fi implementations to a common layer. It includes specialized tooling for secure device commissioning via QR codes and NFC, as well as a comprehensive over-the-air firmware update system for distributing s

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

Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

Apache Hive is a SQL-on-Hadoop data warehouse that enables querying and managing petabytes of data stored in distributed storage such as HDFS and cloud storage services. It provides a familiar SQL interface for batch analytics and reporting, supported by a core set of components including the HiveServer2 Thrift service for remote query execution, the Hive Metastore Service for central metadata management, the Hive ACID Transaction Engine for concurrent read-write operations, and the Hive LLAP Interactive Engine for low-latency analytical processing. The WebHCat REST API offers an HTTP interfac

GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

Algodeck is an open-source collection of flash cards designed for reviewing algorithms, data structures, and system design concepts, specifically curated for technical interview preparation. The project organizes knowledge into atomic question-and-answer pairs and incorporates spaced repetition scheduling to optimize long-term memory retention. The flash card catalog covers a broad range of computer science topics, including classic sorting algorithms like quicksort and mergesort, data structure operations for arrays, trees, heaps, tries, and graphs, as well as bit manipulation techniques for