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Awesome GitHub RepositoriesShared Memory Data Exchange

Mechanisms for high-performance data transfer between processes using zero-copy memory buffers.

Distinguishing note: Focuses on inter-process communication via shared memory rather than general database storage or network protocols.

Explore 74 awesome GitHub repositories matching data & databases · Shared Memory Data Exchange. Refine with filters or upvote what's useful.

Awesome Shared Memory Data Exchange GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • facebook/reactfacebook का अवतार

    facebook/react

    245,669GitHub पर देखें↗

    React एक JavaScript लाइब्रेरी है, जो कॉम्पोनेंट-आधारित आर्किटेक्चर और यूनिडायरेक्शनल डेटा फ्लो का उपयोग करके यूजर इंटरफेस बनाने के लिए है।

    Shares reactive data snapshots across components to ensure consistent state.

    JavaScriptjavascriptuifrontend
    GitHub पर देखें↗245,669
  • vuejs/vuevuejs का अवतार

    vuejs/vue

    209,900GitHub पर देखें↗

    Vue एक प्रगतिशील, घटक-आधारित JavaScript फ्रेमवर्क है जिसे प्रतिक्रियाशील यूजर इंटरफेस और सिंगल-पेज एप्लिकेशन बनाने के लिए डिज़ाइन किया गया है। यह एक घोषणात्मक टेम्पलेट सिस्टम पर केंद्रित है जो HTML को कुशल रेंडर कार्यों में बदलता है, जिससे डेवलपर्स जटिल इंटरफेस को अलग-अलग, पुन: प्रयोज्य इकाइयों में व्यवस्थित कर सकते हैं जो स्वचालित रूप से एप्लिकेशन स्थिति के साथ सिंक होते हैं। फ्रेमवर्क एक निर्भरता-ट्रैकिंग प्रतिक्रियाशीलता सिस्टम के माध्यम से खुद को अलग करता है जो सटीक अपडेट को ट्रिगर करने के लिए रेंडरिंग के दौरान डेटा एक्सेस की निगरानी करता है। यह एक लचीला आर्किटेक्चर प्रदान करता है जो हल्के लाइब्रेरी के रूप में वृद्धिशील अपनाने और पूर्ण-स्तरीय एप्लिकेशन विकास दोनों का समर्थन करता है। डेवलपर्स वैश्विक लॉजिक को इंजेक्ट करने के लिए एक मजबूत प्लगइन-आधारित एक्स्टेंसिबिलिटी मॉडल का लाभ उठा सकते हैं, जबकि फ्रेमवर्क का वर्चुअल DOM सुलह न्यूनतम उत्परिवर्तन (mutations) की गणना करके कुशल इंटरफ़ेस अपडेट सुनिश्चित करता है। अपनी मुख्य रेंडरिंग क्षमताओं से परे, प्रोजेक्ट में एप्लिकेशन स्टेट, URL-आधारित रूटिंग और सर्वर-साइड रेंडरिंग को प्रबंधित करने के लिए टूल का एक व्यापक सूट शामिल है। यह घटक संरचना, सामग्री वितरण और एनीमेशन प्रबंधन के लिए व्यापक समर्थन प्रदान करता है, साथ ही सामान्य कमजोरियों को रोकने के लिए स्वचालित सामग्री एस्केपिंग जैसे अंतर्निहित सुरक्षा उपाय भी प्रदान करता है। फ्रेमवर्क को स्टेटिक विश्लेषण का समर्थन करने के लिए आधिकारिक टाइप घोषणाओं के साथ वितरित किया जाता है और इसे मानक पैकेज मैनेजरों के माध्यम से स्थापित किया जा सकता है या स्क्रिप्ट टैग के माध्यम से सीधे ब्राउज़र वातावरण में एकीकृत किया जा सकता है।

    Synchronizes data across instances by sharing object references for automatic updates.

    TypeScriptframeworkfrontendjavascript
    GitHub पर देखें↗209,900
  • clickhouse/clickhouseClickHouse का अवतार

    ClickHouse/ClickHouse

    48,229GitHub पर देखें↗

    ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

    Enables high-speed data transfer between the engine and external tools using zero-copy buffers to bypass serialization overhead.

    C++aianalyticsbig-data
    GitHub पर देखें↗48,229
  • 0voice/interview_internal_reference0voice का अवतार

    0voice/interview_internal_reference

    37,235GitHub पर देखें↗

    This project is a comprehensive technical interview question bank and reference library designed for software engineering roles at major technology companies. It serves as a study guide and knowledge base covering the core principles of high-performance systems programming and computer science theory. The collection focuses on deep technical domains, including C++ language mastery, distributed systems design, and database engineering. It provides detailed material on consensus protocols, cluster coordination, and the architectural differences between SQL and NoSQL implementations. The resour

    Details high-performance data transfer between separate processes using shared memory segments and pipes.

    Pythoncpuhigh-performanceinterview
    GitHub पर देखें↗37,235
  • lovell/sharplovell का अवतार

    lovell/sharp

    32,340GitHub पर देखें↗

    Sharp is a high-performance image processing library for Node.js. It serves as a native extension and wrapper for the libvips framework, providing tools for image resizing, format conversion, and programmatic data manipulation. The project enables the transformation of images into web-friendly formats such as WebP and AVIF while preserving color profiles and alpha channels. It also provides capabilities for generating blank image buffers with specified dimensions and background colors. The library covers a broad range of image manipulation utilities, including rotation, extraction, compositi

    Implements direct memory data transfer between the Node.js heap and native memory for high-performance image data handling.

    JavaScriptavifcropexif
    GitHub पर देखें↗32,340
  • walter201230/pythonwalter201230 का अवतार

    walter201230/Python

    26,516GitHub पर देखें↗

    Python is a high-level, interpreted programming language designed for readability and versatility. It operates via a bytecode-based virtual machine and manages memory automatically through reference-counting garbage collection. The language supports multiple programming paradigms, including object-oriented, imperative, and functional styles, and provides a comprehensive standard library for system operations, networking, and data handling. The language is distinguished by its dynamic nature, allowing for runtime object introspection and metaclass-driven class creation. It utilizes protocol-ba

    Python facilitates data exchange between threads or processes using messaging mechanisms to coordinate work and share results across execution units.

    Pythonpythonpython3
    GitHub पर देखें↗26,516
  • javascript-tutorial/en.javascript.infojavascript-tutorial का अवतार

    javascript-tutorial/en.javascript.info

    25,344GitHub पर देखें↗

    This project is a comprehensive JavaScript programming tutorial and language reference. It serves as a web development education resource providing instruction on modern language fundamentals, object-oriented design, and advanced asynchronous programming patterns. The resource functions as both a frontend development guide and a technical reference. It covers core language features such as closures, prototypes, promises, and typed arrays, while providing practical lessons on managing browser data and handling network requests. The content spans several key capability areas, including browser

    Teaches the use of fixed-type views over raw binary buffers to handle numeric data.

    HTMLenglishjavascripttutorial
    GitHub पर देखें↗25,344
  • libgdx/libgdxlibgdx का अवतार

    libgdx/libgdx

    24,816GitHub पर देखें↗

    LibGDX is a Java-based framework designed for cross-platform game development, enabling the creation and deployment of 2D and 3D games across desktop, mobile, and web environments from a single codebase. It functions as a comprehensive library that abstracts hardware-accelerated graphics, audio, input, and file system access, providing a unified interface for developers to manage game logic and application lifecycles. The framework distinguishes itself through a high-performance architecture that prioritizes efficiency and native interoperability. It utilizes a batch-oriented graphics pipelin

    Exchanges large data arrays between Java and native code using direct memory buffers to minimize overhead.

    Java2d3dandroid
    GitHub पर देखें↗24,816
  • vectordotdev/vectorvectordotdev का अवतार

    vectordotdev/vector

    22,071GitHub पर देखें↗

    Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network

    Distributes incoming data across parallel workers to automatically adapt throughput to varying volumes.

    Rusteventsforwarderhacktoberfest
    GitHub पर देखें↗22,071
  • huggingface/datasetshuggingface का अवतार

    huggingface/datasets

    21,643GitHub पर देखें↗

    Datasets is a library designed for the management, processing, and sharing of large-scale data collections for machine learning workflows. It functions as both a data processing framework and a versioning platform, providing tools to organize, filter, and transform massive datasets while ensuring reproducibility across research and development teams. The library distinguishes itself by enabling the handling of datasets that exceed available system memory. It utilizes memory-mapped file access, disk-based caching, and lazy iterative streaming to maintain performance when working with large-sca

    Facilitates team collaboration on machine learning benchmarks through shared data repositories.

    Pythonaiartificial-intelligencecomputer-vision
    GitHub पर देखें↗21,643
  • mastra-ai/mastramastra-ai का अवतार

    mastra-ai/mastra

    21,221GitHub पर देखें↗

    Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

    Provides mechanisms for queuing and sequencing agent messages to ensure orderly task execution on shared threads.

    TypeScriptagentsaichatbots
    GitHub पर देखें↗21,221
  • swoole/swoole-srcswoole का अवतार

    swoole/swoole-src

    18,891GitHub पर देखें↗

    Swoole is a coroutine-based concurrency library and IO framework for PHP. It provides a system for building high-performance network servers and applications by bringing asynchronous, event-driven, and coroutine-based concurrency to the PHP runtime. The project distinguishes itself by implementing user-space coroutine scheduling and non-blocking IO interception, which transforms standard blocking network and file operations into asynchronous actions. It further enables high-speed data exchange across multiple PHP processes through shared memory management and specialized data structures. The

    Provides high-speed shared memory data structures like tables and ring buffers for inter-process communication.

    C++
    GitHub पर देखें↗18,891
  • brunodev85/winlatorbrunodev85 का अवतार

    brunodev85/winlator

    17,890GitHub पर देखें↗

    Winlator is an Android-based compatibility tool designed to execute x86 and x86_64 Windows applications on mobile hardware. It functions as a translation environment that bridges the gap between desktop software and ARM-based processors, enabling the execution of programs that lack native mobile versions. The project distinguishes itself by integrating a cross-platform instruction translator with a compatibility layer to manage system calls and machine code. It utilizes user-space containerization to isolate the Windows environment, allowing for the management of dependencies and system resou

    Facilitates high-speed data exchange between the translation engine and emulated applications using shared memory.

    C
    GitHub पर देखें↗17,890
  • ffmpegwasm/ffmpeg.wasmffmpegwasm का अवतार

    ffmpegwasm/ffmpeg.wasm

    17,184GitHub पर देखें↗

    ffmpeg.wasm is a browser-based multimedia processing engine that brings the capabilities of the FFmpeg library directly to the client environment. By utilizing WebAssembly, it enables audio and video transcoding, format conversion, and stream recording to occur entirely within the browser without requiring server-side infrastructure. The library distinguishes itself by executing resource-intensive media tasks in background threads, ensuring that the main user interface remains responsive during complex operations. It manages data through an isolated, in-memory virtual file system, allowing fo

    Enables high-performance data exchange between threads using shared memory buffers to avoid expensive copying.

    Caudioexperimental-featuresffmpeg
    GitHub पर देखें↗17,184
  • prestodb/prestoprestodb का अवतार

    prestodb/presto

    16,711GitHub पर देखें↗

    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

    Writes intermediate data to disk during execution to support memory-intensive operations and ensure large-scale task completion.

    Javabig-datadatahadoop
    GitHub पर देखें↗16,711
  • gpujs/gpu.jsgpujs का अवतार

    gpujs/gpu.js

    15,377GitHub पर देखें↗

    This library is a JavaScript framework for general-purpose computing on graphics processing units. It enables the execution of parallel mathematical operations directly within the browser by offloading data-heavy calculations to graphics hardware. The project functions as a web-based math accelerator that converts standard JavaScript functions into shader code for execution on the graphics processor. It provides a unified interface that detects available graphics APIs and manages data transfer between system and graphics memory. To ensure compatibility across diverse environments, the library

    Manages data transfer between system and graphics memory using structured buffers to minimize latency.

    JavaScriptglslgpgpugpu
    GitHub पर देखें↗15,377
  • hoffstadt/dearpyguihoffstadt का अवतार

    hoffstadt/DearPyGui

    15,217GitHub पर देखें↗

    DearPyGui is a GPU-accelerated, immediate-mode graphical user interface framework for Python. It provides a high-performance toolkit for building interactive desktop applications by leveraging native hardware-accelerated rendering backends across multiple operating systems. By utilizing an immediate-mode execution model, the library offers direct control over the rendering loop and element state, enabling the creation of responsive, dynamic interfaces. The framework distinguishes itself through its ability to handle complex, high-frequency visual updates, making it suitable for real-time data

    Links multiple interface components to shared data sources for automatic, synchronized updates.

    C++cppcross-platformdearpygui
    GitHub पर देखें↗15,217
  • kotlin/kotlinx.coroutinesKotlin का अवतार

    Kotlin/kotlinx.coroutines

    13,703GitHub पर देखें↗

    Kotlinx.coroutines is a library for managing non-blocking background tasks and structured concurrency within the Kotlin programming language. It provides a framework for executing concurrent operations and synchronizing shared state, replacing traditional thread management and complex callback chains with lightweight primitives. The library utilizes a structured concurrency hierarchy to organize hierarchical background tasks, ensuring that lifecycle management, cancellation, and timeout handling propagate automatically to prevent resource leaks. It employs continuation-passing style transform

    Controls access to shared information across threads to prevent race conditions during parallel processing.

    Kotlinasynccoroutineskotlin
    GitHub पर देखें↗13,703
  • sql-js/sql.jssql-js का अवतार

    sql-js/sql.js

    13,632GitHub पर देखें↗

    sql.js is a serverless, in-memory SQL database engine that ports SQLite to WebAssembly for use within a web browser. It provides a JavaScript interface to initialize relational databases, execute SQL queries, and manage structured data without requiring a backend server. The project enables the import and export of database states using typed arrays, allowing in-memory data to be persisted as files. It supports high-precision integer retrieval via BigInt and utilizes prepared statements to increase execution speed and security. The engine includes capabilities for client-side data management

    Uses JavaScript typed arrays to map the database's linear memory and internal state for efficient access.

    JavaScript
    GitHub पर देखें↗13,632
  • microg/gmscoremicrog का अवतार

    microg/GmsCore

    13,682GitHub पर देखें↗

    GmsCore is an open-source Android framework component that functions as a compatibility layer for mobile devices. It acts as a middleware service, providing an implementation of proprietary mobile service interfaces to ensure that applications requiring these components can function on devices where they are not natively installed. The project distinguishes itself by enabling the use of standard mobile applications on devices that lack official proprietary background services. By intercepting and redirecting application requests to local open-source implementations, it allows users to maintai

    Exchanges state information between the service layer and client applications through low-latency memory buffers.

    Javaandroidauthcloud-messaging
    GitHub पर देखें↗13,682
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  3. Shared Memory Data Exchange

सब-टैग एक्सप्लोर करें

  • App Group Data ExchangeExchange of data between app processes using shared storage groups instead of raw shared memory. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: uses persistent file-based shared groups rather than zero-copy memory buffers.
  • Concurrent Data Pipelines1 सब-टैगStructures for managing high-volume data flow between multiple producers and consumers. **Distinct from Shared Memory Data Exchange:** Distinct from shared memory exchange: focuses on the pipeline management aspect of lock-free queues rather than raw memory buffers.
  • Direct Memory Data Transfer3 सब-टैग्सMechanisms for exchanging large data arrays between managed and native memory using direct buffers. **Distinct from Shared Memory Data Exchange:** Distinct from general shared memory exchange: focuses on Java-to-native array transfer.
  • GPU Framework Data ExchangesZero-copy sharing of GPU array data between different deep learning frameworks. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: focuses on GPU array exchange between ML frameworks, not inter-process shared memory.
  • Messaging QueuesMechanisms for passing data between execution units using thread-safe or process-safe messaging structures. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: focuses on message-passing coordination rather than raw memory buffer sharing.
  • Reactive Data Sharing3 सब-टैग्सMechanisms for sharing reactive data objects by reference across components. **Distinct from Shared Memory Data Exchange:** Focuses on reactive object sharing within a single process rather than inter-process memory exchange.
  • Remote Cache Block SharingExchanging metadata and access permissions for memory blocks across distributed nodes. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: focuses on metadata and permission exchange for remote cache blocks rather than local zero-copy buffers.
  • Scratchpad MemoriesUser-managed, low-latency caches within multiprocessors for high-speed data exchange between threads. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: focuses on hardware-level scratchpad caches for thread blocks rather than inter-process communication.
  • Zero-Copy Array ViewsLightweight references to memory buffers that allow slicing and reshaping without copying data. **Distinct from Shared Memory Data Exchange:** Distinct from Shared Memory Data Exchange: focuses on internal array views rather than inter-process communication