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116 repositorios

Awesome GitHub RepositoriesData Snapshotting

Mechanisms for creating point-in-time backups of database state.

Distinguishing note: Focuses on cluster-wide snapshotting for restoration.

Explore 116 awesome GitHub repositories matching data & databases · Data Snapshotting. Refine with filters or upvote what's useful.

Awesome Data Snapshotting GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • firehol/netdataAvatar de firehol

    firehol/netdata

    79,416Ver en GitHub↗

    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

    Supports exporting historical performance data to third-party time-series databases for long-term retention.

    Go
    Ver en GitHub↗79,416
  • milla-jovovich/mempalaceAvatar de milla-jovovich

    milla-jovovich/mempalace

    56,418Ver en GitHub↗

    Mempalace is a local-first long-term memory store for large language models and AI agents. It provides a persistent storage system for verbatim conversation history and agent data, utilizing a local-first knowledge graph to track evolving entity relationships and timelines. The project implements a standardized memory protocol that allows external AI clients to read and write persistent memory via standard input and output. It features a hybrid semantic search engine that combines keyword boosting and reranking to find precise historical information across scoped categories. The system inclu

    Saves periodic session states and transcript backups to capture context before compression.

    Python
    Ver en GitHub↗56,418
  • mempalace/mempalaceAvatar de MemPalace

    MemPalace/mempalace

    55,712Ver en GitHub↗

    Mempalace is a long-term memory management system for large language models that orchestrates the storage and retrieval of conversation history and entity relationships. It functions as a memory orchestrator and Model Context Protocol server, providing AI clients with read and write access to structured knowledge. The system utilizes a temporal knowledge graph to track evolving entity relationships and timelines with validity windows. It employs a hierarchical memory partitioning strategy, organizing data into wings and rooms to isolate specialist agent contexts and restrict semantic searches

    Uses internal hooks to trigger periodic state saves and transcript snapshots to prevent data loss.

    Pythonaichromadbllm
    Ver en GitHub↗55,712
  • gogs/gogsAvatar de gogs

    gogs/gogs

    47,606Ver en GitHub↗

    Gogs es un servicio de Git autohospedado y una plataforma de alojamiento de código colaborativo. Funciona como un gestor de control de versiones que permite a los usuarios almacenar y gestionar el código fuente en su propia infraestructura utilizando protocolos SSH, HTTP y HTTPS. La plataforma se distingue por capacidades de duplicación (mirroring) integrales, actuando como una herramienta para sincronizar y duplicar repositorios y wikis desde proveedores de alojamiento externos a una instancia local. Está diseñada para un despliegue seguro y contenedorizado, admitiendo configuraciones de usuario no root para cumplir con estrictos requisitos de seguridad. Más allá del alojamiento básico, proporciona un conjunto de herramientas de colaboración que incluyen solicitudes de extracción (pull requests), seguimiento de problemas, wikis y revisiones de código por pares. El sistema incorpora automatización del flujo de trabajo a través de webhooks y hooks de Git, gestiona archivos binarios de gran tamaño a través de Large File Storage y ofrece control de acceso granular para la gestión de repositorios privados. El servicio se puede desplegar como una imagen de contenedor para un comportamiento consistente en diferentes entornos de alojamiento.

    Creates snapshots of service data using retention policies to ensure rapid recovery after a system failure.

    Godockergitgo
    Ver en GitHub↗47,606
  • hmbown/codewhaleAvatar de Hmbown

    Hmbown/CodeWhale

    38,468Ver en GitHub↗

    CodeWhale is an AI coding agent orchestrator and development harness designed to coordinate autonomous agents that read, edit, and verify code. It provides a secure environment for AI agents to perform multi-step software engineering tasks, utilizing a sandboxed execution model to isolate shell commands and protect the host system. The system distinguishes itself by spawning multiple independent agents in parallel to handle separate investigation or implementation slices simultaneously. It employs a multi-model gateway to route requests across various cloud APIs and local servers, and utilize

    Captures temporary project snapshots to restore the codebase to a previous turn without altering git history.

    Rustclideepseekllm
    Ver en GitHub↗38,468
  • junegunn/vim-plugAvatar de junegunn

    junegunn/vim-plug

    35,685Ver en GitHub↗

    vim-plug is a plugin manager for the Vim text editor that functions as a git-based dependency manager and configuration bootstrapper. It downloads and organizes external plugin packages from remote repositories to extend the editor's functionality. The project acts as a lazy-loading orchestrator to reduce editor startup time by deferring the loading of plugins until specific commands or file types are encountered. It enables version pinning by allowing plugins to be fetched using specific git branches, tags, or commit hashes. The manager provides a framework for plugin installation, lifecycl

    Generates a script that captures the current state of all installed plugins for easy restoration or sharing.

    Vim Scriptvim
    Ver en GitHub↗35,685
  • qdrant/qdrantAvatar de qdrant

    qdrant/qdrant

    32,372Ver en GitHub↗

    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

    Backs up data by creating and downloading collection snapshots from individual cluster nodes.

    Rustai-searchai-search-engineembeddings-similarity
    Ver en GitHub↗32,372
  • humansignal/label-studioAvatar de HumanSignal

    HumanSignal/label-studio

    27,619Ver en GitHub↗

    Label Studio is a multi-modal data annotation platform designed to create and manage high-quality training datasets for machine learning. It functions as a self-hosted, containerized environment that supports secure, private deployments, including air-gapped configurations. The platform provides a centralized workspace for labeling diverse media types, such as images, text, audio, and time-series data, to support supervised and reinforcement learning workflows. The platform distinguishes itself through deep integration with machine learning backends, enabling active learning loops, automated

    Enables asynchronous creation and retrieval of annotation data snapshots to handle large-scale projects without performance degradation.

    TypeScriptannotationannotation-toolannotations
    Ver en GitHub↗27,619
  • esengine/deepseek-reasonixAvatar de esengine

    esengine/DeepSeek-Reasonix

    24,096Ver en GitHub↗

    DeepSeek-Reasonix is an autonomous software engineering framework and terminal-based AI IDE designed to coordinate large language models for complex programming tasks. It functions as a multi-session agent that utilizes a split planner and executor workflow to break down and implement technical objectives. The system distinguishes itself through a specialized focus on session optimization and extensibility. It employs prefix caching and append-only history to reduce token consumption and latency during long sessions. It further extends its capabilities by integrating external tool servers via

    Provides state restoration via code snapshots to revert the project to previous stable versions.

    Goagentagent-frameworkai-agent
    Ver en GitHub↗24,096
  • apify/crawleeAvatar de apify

    apify/crawlee

    24,002Ver en GitHub↗

    Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob

    Maintains a time-windowed history of system state snapshots with automatic pruning of expired entries.

    TypeScriptapifyautomationcrawler
    Ver en GitHub↗24,002
  • vonng/ddiaAvatar de Vonng

    Vonng/ddia

    22,648Ver en GitHub↗

    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

    Provides mechanisms for creating point-in-time backups of database state.

    Pythonbookdatabaseddia
    Ver en GitHub↗22,648
  • 2025emma/vibe-coding-cnAvatar de 2025Emma

    2025Emma/vibe-coding-cn

    21,712Ver en GitHub↗

    This project functions as an orchestration framework for AI-driven software development, providing a structured environment to manage, iterate, and execute complex prompt chains. It serves as a centralized workspace that integrates AI models with local terminal tools and configuration settings to standardize the entire development lifecycle from initial requirements to final implementation. The platform distinguishes itself through its focus on recursive prompt evolution and multilingual support. It employs iterative loops to refine AI instructions, ensuring higher precision in generated outp

    Captures project states and configuration files to ensure development progress remains recoverable.

    Python
    Ver en GitHub↗21,712
  • qax-os/excelizeAvatar de qax-os

    qax-os/excelize

    20,682Ver en GitHub↗

    Excelize is a library for reading and writing spreadsheet files in the Office Open XML format. It provides a comprehensive suite of tools for programmatically creating, modifying, and analyzing workbooks, worksheets, and cell data, ensuring compatibility across various office software suites through structured XML serialization. The library distinguishes itself with a built-in formula calculation engine that evaluates complex mathematical and logical expressions directly against workbook data. It also features a memory-mapped streaming architecture, which allows for the efficient processing o

    Captures system state snapshots at regular intervals for data redundancy and recovery.

    Goagentaianalytics
    Ver en GitHub↗20,682
  • claude-code-best/claude-codeAvatar de claude-code-best

    claude-code-best/claude-code

    20,272Ver en GitHub↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Maintains content-hashed file snapshots to enable atomic rollbacks of codebase changes made by agents.

    TypeScript
    Ver en GitHub↗20,272
  • nats-io/nats-serverAvatar de nats-io

    nats-io/nats-server

    20,076Ver en GitHub↗

    NATS Server is a high-performance, lightweight messaging system designed for cloud-native applications, edge computing, and distributed microservices. It functions as a distributed publish-subscribe broker that routes messages using hierarchical, dot-separated subject strings, enabling decoupled communication between services without requiring centralized broker lookups. The system supports core messaging patterns including asynchronous publish-subscribe, request-reply, and load-balanced queue processing. The platform distinguishes itself through a decentralized architecture that eliminates t

    Facilitates data durability and disaster recovery by creating point-in-time snapshots of stream configurations and payloads.

    Gocloudcloud-computingcloud-native
    Ver en GitHub↗20,076
  • rrweb-io/rrwebAvatar de rrweb-io

    rrweb-io/rrweb

    19,775Ver en GitHub↗

    rrweb is a DOM session recording library and serialization framework used to record and replay web sessions. It converts the state of a web page into a serializable JSON data structure and tracks mutations to reconstruct user interactions within a replay engine. The system distinguishes itself by using a sandboxed iframe for reconstruction to isolate replayed content, preventing script execution and form submissions. It ensures visual consistency through CSS inline-style flattening and provides sensitive data masking to prevent private information from being captured. The project covers a br

    Provides periodic full DOM snapshots to allow jumping to any point in a recorded session.

    TypeScript
    Ver en GitHub↗19,775
  • subquery/subqlAvatar de subquery

    subquery/subql

    18,791Ver en GitHub↗

    Subql is a blockchain data indexing framework and TypeScript-based indexer used to extract raw blockchain events and transactions and transform them into structured, queryable data entities. It functions as a data API and a tool for building decentralized application backends, providing a query interface for type-safe access to indexed blockchain data. The project includes an AI-powered query engine that utilizes large language models to translate natural language questions into structured GraphQL queries. This system can orchestrate multi-step queries by breaking down complex requests into s

    Tracks the progress of indexed blocks to facilitate the efficient reindexing of partial data subsets.

    TypeScript
    Ver en GitHub↗18,791
  • frdel/agent-zeroAvatar de frdel

    frdel/agent-zero

    18,223Ver en GitHub↗

    Agent Zero is an LLM agent framework and multi-agent orchestrator that provides an AI-powered interface for operating system tasks. It functions as a containerized AI workspace, allowing large language models to interact with a filesystem and terminal within an isolated Linux environment. The system distinguishes itself through a hierarchical orchestration model that decomposes complex goals by spawning specialized sub-agents to collaborate and consolidate results. It features a plugin-based architecture for extending capabilities via a community plugin hub, a custom skills system, and extern

    Captures the state of the workspace at specific intervals to allow difference inspection and environment rollback.

    Python
    Ver en GitHub↗18,223
  • etsy/statsdAvatar de etsy

    etsy/statsd

    18,046Ver en GitHub↗

    StatsD is a network-based metrics daemon and aggregator that collects application performance data, such as counters and timers, for periodic delivery to backend services. It functions as system monitoring middleware, receiving telemetry via UDP to minimize performance overhead on monitored services. The system acts as a distributed metrics router, employing consistent hashing to distribute data points across clusters and ensure aggregation accuracy. It includes cluster health monitoring to track node availability and automatically recalculate routing paths when services go offline. The proj

    Pushes aggregated metric snapshots to external storage services at a defined frequency using a scheduled timer.

    JavaScript
    Ver en GitHub↗18,046
  • statsd/statsdAvatar de statsd

    statsd/statsd

    18,046Ver en GitHub↗

    StatsD is a metrics aggregator and UDP collection server that collects system counters and timers. It functions as a time-series data forwarder, receiving high-frequency metric updates via a lightweight line protocol and summarizing them before flushing the data to a backend. The project features a pluggable metrics backend framework, allowing aggregated statistics to be routed to various third-party monitoring services or time-series databases such as Graphite. It supports horizontal scaling and high availability through a proxy ring distribution system that forwards incoming packets across

    Exports aggregated telemetry snapshots to upstream storage backends after a set flush interval.

    JavaScriptgraphitejavascriptmetrics
    Ver en GitHub↗18,046
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Explorar subetiquetas

  • Annotation SnapshotsAsynchronous point-in-time captures of annotation data for large-scale project management. **Distinct from Data Snapshotting:** Distinct from general database snapshotting: focuses on project-specific annotation data snapshots to prevent timeouts.
  • Data Set ComparisonsComparing serialized data sets from different test runs to detect unintended state changes. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on the comparison logic between two snapshots rather than just the backup mechanism.
  • Differencing Snapshot ChainsStoring snapshots as a sequence of read-only layers to enable efficient incremental backups and rollbacks. **Distinct from Data Snapshotting:** Focuses on the layered data model (differencing layers) rather than general snapshotting mechanisms.
  • Historical6 sub-etiquetasRecords changes to source data over time to track historical state. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on slowly changing dimensions and historical state tracking rather than cluster-wide backups.
  • Periodic Snapshots7 sub-etiquetasAutomated capture of system state at regular intervals for performance tracking. **Distinct from Data Snapshotting:** Distinct from cluster-wide database snapshotting: focuses on periodic system state capture for observability.
  • Snapshot HooksTriggers custom SQL commands before or after the snapshot process to manage database state. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on lifecycle hooks during the snapshot process rather than the snapshot mechanism itself.
  • Snapshot Metadata Retrievers2 sub-etiquetasQueries system metadata to locate and filter historical data snapshots. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on querying metadata about existing snapshots rather than the snapshotting mechanism itself.
  • State Snapshots22 sub-etiquetasCapturing time-windowed system state snapshots to track changes or recover previous configurations. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on temporal state tracking and automatic pruning of outdated snapshots rather than full database backups.
  • Stream SnapshottersTools for creating point-in-time backups of stream configurations and message payloads. **Distinct from Data Snapshotting:** Distinct from Data Snapshotting: focuses on stream-specific durability and disaster recovery rather than general database state.
  • System State SnapshottingCapturing point-in-time views of active system resources like processes and sockets. **Distinct from State Snapshots:** Distinct from State Snapshots: focuses on volatile runtime system state rather than configuration or database state.
  • Viewport Snapshots3 sub-etiquetasMechanisms for capturing the current text state of a terminal pane as a point-in-time snapshot. **Distinct from Data Snapshotting:** Distinct from database snapshotting: focuses on terminal viewport state rather than cluster-wide data backups.