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840 个仓库

Awesome GitHub RepositoriesData Persistence and Storage

Technologies and architectures dedicated to the durable storage and long-term management of digital information.

Explore 840 awesome GitHub repositories matching data & databases · Data Persistence and Storage. Refine with filters or upvote what's useful.

Awesome Data Persistence and Storage GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • donnemartin/system-design-primerdonnemartin 的头像

    donnemartin/system-design-primer

    353,387在 GitHub 上查看↗

    这是一个关于分布式系统架构和后端基础设施设计的综合教育资源和学习指南。它为掌握设计复杂软件系统所需的扩展性、可靠性和性能原则提供了结构化课程。 该仓库通过提供一种系统化的技术面试准备方法脱颖而出,结合了设计模式、架构权衡和间隔重复工具,帮助用户记忆复杂概念。它强调约束驱动的分析,教授用户在起草架构设计时如何评估延迟、一致性和可用性等相互竞争的需求。 内容涵盖了广泛的系统设计能力,包括数据库扩展、流量管理和基础设施优化策略。它详细介绍了水平扩展、多层缓存、异步通信和服务发现技术,同时还提供了用于执行资源估算和容量规划的框架。 文档以学习指南的形式组织,为后端工程和大规模系统设计的基础知识提供了系统化的路径。

    Details mechanisms for storing frequently accessed data in memory to reduce latency and backend processing requirements.

    Pythondesigndesign-patternsdesign-system
    在 GitHub 上查看↗353,387
  • vinta/awesome-pythonvinta 的头像

    vinta/awesome-python

    303,207在 GitHub 上查看↗

    这是一个全面的、由社区策划的目录,组织了庞大的 Python 软件库、框架和工具生态。它作为一个中心化知识库,旨在促进生态导航并加速开发者在整个软件开发生命周期中的发现过程。 该目录通过提供按技术领域分类的结构化资源索引脱颖而出,范围从基础开发工具到专业工程领域。它涵盖了人工智能、数据科学、Web 开发和基础设施管理等高级能力,使开发者能够为特定的技术挑战识别经过验证的解决方案。 该项目涵盖了广泛的能力领域,包括依赖管理、静态代码分析和自动化测试工具。它还编目了用于持久数据存储、云基础设施编排和接口开发的资源,为构建和维护复杂软件系统提供了统一的参考。

    Boost system performance by memoizing frequently accessed data within memory-efficient storage structures.

    Pythonawesomecollectionspython
    在 GitHub 上查看↗303,207
  • torvalds/linuxtorvalds 的头像

    torvalds/linux

    237,355在 GitHub 上查看↗

    Linux 内核是一个单体操作系统核心,管理跨不同计算架构的硬件资源、内存和进程调度。它为应用程序执行提供了一个标准化的、符合 POSIX 的环境,同时维护了一个模块化的驱动程序框架,允许动态加载和移除硬件接口。 该项目以其高性能并发工具包而著称,该工具包利用无锁同步原语和读取-复制-更新(RCU)机制来管理多核环境中的共享数据访问。它包含了一套全面的内核跟踪和仪表化套件,能够对系统事件、函数执行和延迟指标进行非侵入式监控。此外,内核强制执行严格的接口稳定性保证和生命周期跟踪,以确保依赖应用程序的向后兼容性。 除了核心身份外,该系统还包括用于硬件抽象、网络协议实现和安全策略执行的广泛能力。它通过电源状态管理、嵌入式系统优化和基于固件的引导过程支持专业工程需求。该架构还具有用于内存分析、系统执行验证和并发编程模型验证的强大诊断框架。 源代码仓库提供了一个完整的构建系统,用于将代码转换为可执行的二进制镜像,包括用于内核功能选择和配置优化的工具,以针对特定硬件需求定制输出。

    Manages filesystem operations to provide consistent data access and storage organization across physical media.

    C
    在 GitHub 上查看↗237,355
  • trimstray/the-book-of-secret-knowledgetrimstray 的头像

    trimstray/the-book-of-secret-knowledge

    228,641在 GitHub 上查看↗

    该项目作为一个中心化的、社区驱动的技术知识和管理资源仓库。它提供了一个结构化的分类体系,将分散的信息聚合到一个可搜索的框架中,支持系统管理员和网络安全从业者的持续学习和快速问题解决。通过映射跨越进攻性安全、基础设施管理和软件开发的资源,它为技能获取和专业参考提供了统一路径。 该项目由命令行优先的设计理念定义,优先考虑基于终端的实用程序和可脚本化的接口,以促进高效的系统管理和可重复的安全工作流。它通过平台无关的方法脱颖而出,维护在不同类 Unix 和云环境中保持适用的文档和操作指南。这种模块化的工具链集成允许用户组合针对特定管理或安全任务定制的自定义环境。 该仓库涵盖了广泛的能力领域,包括用于系统审计、网络管理和基础设施加固的综合工具包。它为网络安全技能发展提供了结构化的学习路径,范围从道德黑客实验室和渗透测试标准到漏洞评估和系统配置最佳实践。该集合还包含广泛的生产力工具、诊断实用程序和教育材料,旨在简化日常维护并增强整体安全态势。

    Navigate and manage file systems through terminal-based interfaces that simplify directory operations.

    awesomeawesome-listbsd
    在 GitHub 上查看↗228,641
  • affaan-m/eccaffaan-m 的头像

    affaan-m/ECC

    221,981在 GitHub 上查看↗

    ECC 是一个 LLM 智能体编排框架和跨平台 AI 工具套件,旨在协调多模型工作流。它提供了一个用于管理专业智能体角色、可复用技能和结构化规划的系统,以在不同的 AI 驱动代码编辑器中执行复杂的软件开发任务。 该项目作为模型上下文协议(Model Context Protocol)管理器脱颖而出,提供了一个配置层来集成外部服务器并审计工具执行。它进一步实现了一个智能体安全沙箱,限制敏感文件访问并扫描密钥泄露,以保护自主工作流。 该框架涵盖了广泛的能力领域,包括带有测试驱动开发护栏的 AI 编码工作流自动化、通过智能路由实现模型成本优化以及状态隔离的内存管理。它还包括用于强制执行特定语言编码标准和管理跨各种集成开发环境的智能体行为的工具。 该系统通过命令行界面进行管理,该界面处理工具安装、配置修复和工具预设的部署。

    Manages the persistent storage of session summaries and learned skills under configurable root directories.

    JavaScript
    在 GitHub 上查看↗221,981
  • significant-gravitas/autogptSignificant-Gravitas 的头像

    Significant-Gravitas/AutoGPT

    184,973在 GitHub 上查看↗

    AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, including task scheduling, execution monitoring, and configuration management, while offering a marketplace for discovering and sharing community-built workflows. The project includes a legacy framework for command-line agent execution and an extensible component system for devel

    Enables persistent file system interactions including directory navigation, reading, and writing with configurable storage paths.

    Pythonaiartificial-intelligenceautonomous-agents
    在 GitHub 上查看↗184,973
  • langchain-ai/langchainlangchain-ai 的头像

    langchain-ai/langchain

    139,458在 GitHub 上查看↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    Organize directory hierarchies to manage machine-specific state and persistent application data effectively.

    Pythonagentsaiai-agents
    在 GitHub 上查看↗139,458
  • chalarangelo/30-seconds-of-codeChalarangelo 的头像

    Chalarangelo/30-seconds-of-code

    128,121在 GitHub 上查看↗

    30-seconds-of-code is a comprehensive knowledge base and programming snippet library designed to support software engineering education and professional development. It provides a curated collection of reusable code units and technical guides that help developers master core language mechanics, design patterns, and architectural philosophies. The project distinguishes itself by offering a wide-ranging library of algorithmic solutions and web development patterns that are organized into modular, independently testable units. It emphasizes functional programming paradigms and declarative logic,

    Provides tools for serializing and persisting data to the local file system.

    JavaScriptastroawesome-listcss
    在 GitHub 上查看↗128,121
  • excalidraw/excalidrawexcalidraw 的头像

    excalidraw/excalidraw

    125,451在 GitHub 上查看↗

    This project is a virtual whiteboard component and vector graphics editor designed for creating diagrams with a hand-drawn aesthetic. It provides a canvas-based drawing engine that can be embedded directly into web applications, allowing users to manipulate shapes, upload images, and export visual data into standard formats like PNG, SVG, or JSON. The platform distinguishes itself through a real-time synchronization layer that supports multi-user collaboration across distributed environments. This engine utilizes end-to-end encryption to secure shared sessions and employs a local-first data p

    Leverages browser-based storage to maintain application state locally, ensuring data availability and persistence even during offline operation.

    TypeScriptcanvascollaborationdiagrams
    在 GitHub 上查看↗125,451
  • kubernetes/kuberneteskubernetes 的头像

    kubernetes/kubernetes

    123,197在 GitHub 上查看↗

    Kubernetes is a distributed container orchestration platform that automates the deployment, scaling, and management of containerized applications across clusters of computing nodes. It functions as a declarative infrastructure controller, utilizing a control loop architecture that continuously monitors the current system state against user-defined configurations to ensure desired operational outcomes. The system relies on a centralized API-driven interface and a replicated key-value store to maintain a consistent source of truth for all cluster objects. The platform distinguishes itself throu

    Maintains a consistent, replicated data store that serves as the reliable source of truth for distributed system states.

    Gocncfcontainersgo
    在 GitHub 上查看↗123,197
  • immich-app/immichimmich-app 的头像

    immich-app/immich

    104,236在 GitHub 上查看↗

    Immich is a self-hosted media management platform designed to provide a centralized, private repository for photos and videos. It functions as a comprehensive system for organizing, backing up, and viewing personal media collections across mobile devices, web browsers, and external storage locations. By maintaining full control over data ownership and storage infrastructure, the platform ensures that users retain sovereignty over their digital assets. The system distinguishes itself through a distributed architecture that coordinates background media synchronization, real-time filesystem moni

    Mounts external storage volumes to provide containerized services with the necessary filesystem access for indexing media libraries.

    TypeScriptbackup-toolfluttergoogle-photos
    在 GitHub 上查看↗104,236
  • pytorch/pytorchpytorch 的头像

    pytorch/pytorch

    100,814在 GitHub 上查看↗

    PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic differentiation system that allows for flexible, non-static graph execution. The framework is designed for deep integration with Python, enabling natural usage alongside standard scientific computing ecosystems. It distinguishes itself through a comprehensive distributed training sui

    Persists tensors and complex data structures to disk through native loading and saving mechanisms.

    Pythonautograddeep-learninggpu
    在 GitHub 上查看↗100,814
  • chatgptnextweb/nextchatChatGPTNextWeb 的头像

    ChatGPTNextWeb/NextChat

    88,256在 GitHub 上查看↗

    NextChat is a self-hosted web application that provides a unified interface for interacting with multiple large language models. It functions as a conversational platform where users can manage and switch between diverse AI providers through configurable API backends, maintaining full control over their data and infrastructure. The platform features a persistent session layer designed to handle long-running dialogues by managing message history and context. It distinguishes itself through a structured prompt engineering environment that allows for the development and application of templates

    Utilizes browser-based storage to maintain chat logs and user preferences for offline access.

    TypeScriptcalclaudechatgptclaude
    在 GitHub 上查看↗88,256
  • macrozheng/mallmacrozheng 的头像

    macrozheng/mall

    83,878在 GitHub 上查看↗

    This project is an enterprise-grade Java framework designed for building scalable, full-stack e-commerce applications. It provides a comprehensive foundation for microservice-based distributed architectures, enabling the development of complex retail platforms that include product management, order processing, and secure user authentication. By leveraging modular service patterns and centralized API gateways, the framework supports the construction of resilient systems that decompose monolithic business logic into independent, manageable services. The platform distinguishes itself through a r

    Executes administrative tasks for object storage buckets, file transfers, and policy configurations directly through a terminal interface.

    Javadockerelasticsearchelk
    在 GitHub 上查看↗83,878
  • firehol/netdatafirehol 的头像

    firehol/netdata

    79,416在 GitHub 上查看↗

    Netdata is a real-time infrastructure monitoring tool and multi-node observability platform. It functions as a high-resolution monitoring agent, log and metric aggregator, and time-series database designed to provide full-stack visibility into server health. The system is distinguished by its per-second metric sampling and zero-configuration auto-discovery, which allows for immediate infrastructure tracking upon installation. It utilizes edge-based machine learning and unsupervised models to detect system anomalies and abnormal metric patterns locally on each node. For distributed environment

    Provides an efficient time-series database optimized for rapid retrieval and analysis of collected metrics.

    Go
    在 GitHub 上查看↗79,416
  • netdata/netdatanetdata 的头像

    netdata/netdata

    79,176在 GitHub 上查看↗

    Netdata is a distributed observability platform designed for real-time infrastructure monitoring and performance tracking. It functions as a high-frequency agent that collects system, container, and application metrics with per-second precision, providing both local visualization and centralized aggregation across complex, multi-cloud environments. The platform distinguishes itself through edge-based intelligence, utilizing local machine learning models to automatically detect performance anomalies without requiring manual configuration or external query engines. Its architecture prioritizes

    Persists high-resolution telemetry data directly on the host filesystem to ensure continuous availability during network outages.

    Caialertingcncf
    在 GitHub 上查看↗79,176
  • doocs/advanced-javadoocs 的头像

    doocs/advanced-java

    78,987在 GitHub 上查看↗

    This project is a comprehensive Java backend engineering guide and technical reference focused on high-concurrency design, distributed systems, and microservices architecture. It provides detailed strategies for decomposing monolithic applications, managing service discovery, and implementing the architectural patterns required for scalable backend environments. The repository distinguishes itself through an extensive collection of big data algorithmic references and database scaling strategies. It covers memory-efficient techniques for analyzing massive datasets, such as Top-K element extrac

    Implements inverted index engines to map keywords to document identifiers for rapid distributed full-text search.

    Javaadvanced-javadistributed-search-enginedistributed-systems
    在 GitHub 上查看↗78,987
  • openhands/openhandsOpenHands 的头像

    OpenHands/OpenHands

    77,330在 GitHub 上查看↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system enables agents to autonomously navigate codebases, implement features, and resolve issues through iterative reasoning and tool execution. The platform distinguishes itself through a model-agnostic orchestrator that connects diverse language models to a unified tool registry. It

    Store conversation history in structured directory formats with sequentially indexed event files for granular data access.

    Pythonagentartificial-intelligencechatgpt
    在 GitHub 上查看↗77,330
  • elastic/elasticsearchelastic 的头像

    elastic/elasticsearch

    77,012在 GitHub 上查看↗

    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

    Organizes schema-flexible data into searchable documents across distributed storage environments.

    Javaelasticsearchjavasearch-engine
    在 GitHub 上查看↗77,012
  • awesomedata/awesome-public-datasetsawesomedata 的头像

    awesomedata/awesome-public-datasets

    75,979在 GitHub 上查看↗

    This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that

    Presents datasets related to global transportation systems, including traffic, logistics, and transit data.

    aaron-swartzawesome-public-datasetsdatasets
    在 GitHub 上查看↗75,979
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  1. Home
  2. Data & Databases
  3. Data Engineering and Infrastructure
  4. Data Persistence and Storage

探索子标签

  • Checkpoints and RecoveryMechanisms for creating consistent snapshots of data to enable rapid recovery after system restarts. **Distinct from Data Persistence and Storage:** Focuses on the recovery process via checkpoints rather than general long-term storage architecture
  • Contract Storage TieringManagement of contract state across different longevity tiers including persistent, instance, and temporary storage. **Distinct from Data Persistence and Storage:** Specific to smart contract runtime state rather than general data persistence or hardware tiering
  • Cross-Token Key-Value StoresPersistent key-value storage that can be shared and reused across different webhook endpoints and workflows. **Distinct from Data Persistence and Storage:** Distinct from Data Persistence and Storage: focuses on shared key-value storage across multiple endpoints rather than general durable storage.
  • Data Persistence Management10 个子标签Systems that manage the lifecycle and scheduling of data writing operations to ensure reliable storage.
  • Data Persistence Strategies5 个子标签Approaches for ensuring data remains available and consistent across system restarts or local storage environments.
  • Data Storage29 个子标签Components and utilities that facilitate the saving, retrieving, and managing of data within an application environment.
  • Data Storage Architectures10 个子标签Structural designs and patterns that define how data is organized and accessed within a storage system.
  • Data Storage Layers4 个子标签Software abstractions that provide a dedicated interface for interacting with underlying database or storage systems.
  • Delivery AcknowledgementsMechanisms for confirming data persistence or delivery to upstream clients. **Distinct from Data Persistence and Storage:** Distinct from general persistence: focuses on the acknowledgement handshake protocol.
  • Filesystem Abstractions3 个子标签Components focused on low-level file system logic, management, and containerized volume mounting rather than general data storage.
  • Hybrid Persistence EnginesStorage architectures that combine memory-based performance with disk-based durability. **Distinct from Data Persistence and Storage:** Focuses on the combination of memory and disk for performance, distinct from general persistence.
  • Near Real-Time StorageStorage architectures that optimize for immediate searchability of ingested data using memory buffers and logs. **Distinct from Data Persistence and Storage:** Distinct from Data Persistence and Storage: specifically focuses on the low-latency gap between ingestion and visibility, whereas the parent covers general durability.
  • Persistence & Durability3 个子标签Mechanisms that ensure data remains intact and accessible over time, even during system failures or interruptions.
  • Persistence Integration Tests2 个子标签Automated verification of database and cache operations against live storage instances. **Distinct from Data Persistence and Storage:** Distinct from Data Persistence and Storage: focuses on the validation of persistence operations rather than the storage technology itself.
  • Persistence-Ignorant ArchitecturesArchitectural patterns where business logic remains decoupled from specific database schemas or storage technologies. **Distinct from Data Persistence and Storage:** Distinct from general data persistence: focuses on the architectural decoupling of domain logic from storage, rather than the storage technology itself.
  • Specialized Storage Engines3 个子标签High-performance storage backends optimized for specific data structures like inverted indices or distributed key-value consensus.
  • Storage Command-Line InterfacesCLI tools for managing storage buckets and policies.
  • Storage Driver AbstractionsInterchangeable backend implementations for persisting application data and sessions. **Distinct from Data Persistence and Storage:** Focuses on the driver-based abstraction layer for persistence, rather than general storage technologies.
  • Storage Solutions2 个子标签Infrastructure platforms designed to store large volumes of data, typically in cloud or object-based environments.
  • Task List PersistenceDurable storage specifically for user-defined task lists and their completion status. **Distinct from Data Persistence and Storage:** Distinct from general data persistence by focusing on the specific domain of to-do list items.