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11 Repos

Awesome GitHub RepositoriesDistributed Cache Synchronizers

Mechanisms that use backplanes to notify distributed nodes of cache changes to ensure consistency.

Distinct from Distributed Session Caching: Distinct from Distributed Session Caching: synchronizes any cached data via backplane, not just user sessions.

Explore 11 awesome GitHub repositories matching data & databases · Distributed Cache Synchronizers. Refine with filters or upvote what's useful.

Awesome Distributed Cache Synchronizers GitHub Repositories

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  • dtm-labs/dtmAvatar von dtm-labs

    dtm-labs/dtm

    10,881Auf GitHub ansehen↗

    dtm is a distributed transaction framework and polyglot transaction coordinator designed to maintain data consistency across microservices. It functions as a Saga orchestration engine and a two-phase message coordinator, ensuring that multi-service operations either succeed completely or roll back to a consistent state. The project distinguishes itself by supporting multiple consistency patterns, including Saga, TCC, XA, and outbox patterns, allowing users to select the appropriate model for their specific application requirements. It provides a polyglot integration layer via HTTP and gRPC, e

    Uses a two-phase message pattern to atomically update the database and asynchronously update the cache for eventual consistency.

    Gocadencecsharpdatabase
    Auf GitHub ansehen↗10,881
  • go-xorm/xormAvatar von go-xorm

    go-xorm/xorm

    6,628Auf GitHub ansehen↗

    xorm is a relational mapper and object-relational mapping tool for Go. It translates Go structures into SQL queries and maps database rows back into native objects, providing a multi-dialect database driver that supports MySQL, PostgreSQL, SQLite, Oracle, SQL Server, and TiDB. The project features a read-write splitting manager that routes modification requests to a primary database and read requests to replicas. It includes a database schema synchronizer to automatically align table structures and indexes with application data models, as well as a fluent SQL query builder for constructing co

    Ensures consistency between in-memory object caches and the database after record modifications.

    Gogolangmssqlmysql
    Auf GitHub ansehen↗6,628
  • yujiosaka/headless-chrome-crawlerAvatar von yujiosaka

    yujiosaka/headless-chrome-crawler

    5,643Auf GitHub ansehen↗

    This project is a distributed headless Chrome web crawler and data extraction framework. It functions as a JavaScript rendering engine that uses a headless browser to process dynamic pages, extracting structured data from websites that require JavaScript execution. The system is designed for scalable data collection across multiple nodes, using distributed task synchronization and shared caches to prevent duplicate work. It distinguishes itself through the ability to emulate specific client environments by configuring user agents and viewport dimensions, while capturing visual evidence such a

    Uses distributed cache synchronizers to track requested URLs across multiple servers and prevent duplicate work.

    JavaScript
    Auf GitHub ansehen↗5,643
  • alibaba/jetcacheAvatar von alibaba

    alibaba/jetcache

    5,590Auf GitHub ansehen↗

    JetCache ist ein Java-Caching-Framework, das eine einheitliche Schnittstelle für die Verwaltung von Anwendungsdaten bereitstellt. Es fungiert als Two-Level-Cache-Manager, der lokalen In-Memory-Speicher und entfernte verteilte Caches koordiniert, um Netzwerklatenz zu reduzieren und Abrufgeschwindigkeiten zu verbessern. Das Projekt zeichnet sich durch seine deklarative Caching-Bibliothek aus, die Annotationen verwendet, um die Speicherung, den Ablauf und die Invalidierung von Methodenergebnissen zu automatisieren. Es beinhaltet einen verteilten Cache-Synchronisierer, um die Konsistenz durch die Invalidierung lokaler Einträge über Cluster-Instanzen hinweg zu wahren, sowie ein verteiltes Sperr-Tool zur Koordinierung des Zugriffs auf gemeinsam genutzte Ressourcen. Das Framework deckt ein breites Spektrum an Leistungs- und Stabilitätsfunktionen ab, einschließlich nicht-blockierendem asynchronem Abruf, automatischem Hintergrund-Cache-Refreshing und Request-Collapsing, um Cache-Penetration zu verhindern. Es bietet zudem programmatisches Cache-Management, austauschbare Serialisierungsstrategien und Sicherheitsfunktionen wie Allow-List-Deserialisierungsfilterung.

    Broadcasts invalidation messages across a cluster to keep local memory caches consistent.

    Javacachejavajcache
    Auf GitHub ansehen↗5,590
  • permitio/opalAvatar von permitio

    permitio/opal

    5,469Auf GitHub ansehen↗

    Opal ist eine Engine für die Richtlinienverteilung und ein Synchronisierer für Echtzeit-Autorisierungsdaten. Sie dient als Management-Ebene für das Deployment und die Überwachung verteilter Richtlinien-Engines, wie OPA und Cedar, über Microservices-Architekturen hinweg. Das Projekt zentralisiert die Verwaltung von Richtlinien und Daten bei gleichzeitigem Deployment dezentraler Entscheidungspunkte. Das System zeichnet sich dadurch aus, dass es Richtliniencode, der über Versionskontrolle verwaltet wird, von Autorisierungsdaten entkoppelt, die aus externen Datenbanken und APIs abgerufen werden. Es verwendet ein Pub/Sub-basiertes Status-Verteilungsmodell, um sofortige Updates über WebSockets und Webhooks an Agenten zu pushen, wodurch sichergestellt wird, dass dezentrale Agenten einen synchronisierten Status beibehalten, ohne auf periodisches Polling angewiesen zu sein. Die Plattform deckt weitreichende Funktionen ab, einschließlich Multi-Tenant-Richtlinienisolierung durch Scoped-Distribution, Agenten-Gesundheitsüberwachung mit Liveness-Probes und der Orchestrierung von Richtlinien-Engines als Sidecars. Sie bietet zudem Mechanismen für lokales Caching zur Unterstützung des Offline-Betriebs und sichere Client-Authentifizierung mittels signierter Tokens. Der Administrationsserver kann als Container oder innerhalb eines Kubernetes-Clusters mittels eines Paketmanagers bereitgestellt werden.

    Automatically populates local policy engine caches by fetching application state from external databases and APIs.

    Pythonauthorizationcedarhacktoberfest
    Auf GitHub ansehen↗5,469
  • cerbos/cerbosAvatar von cerbos

    cerbos/cerbos

    4,460Auf GitHub ansehen↗

    Cerbos is an open-source authorization service that provides a centralized, language-agnostic engine for managing access control. It functions as a policy-as-code platform, allowing teams to define, test, and distribute authorization rules using declarative YAML or JSON configurations. By decoupling access logic from application code, it enables consistent permission enforcement across diverse service stacks. The project distinguishes itself through its ability to translate high-level authorization policies into native database query filters. This capability allows applications to enforce sec

    Persists authorization policies to local disk to ensure continued operation during network outages.

    Goaccess-controlauthorizationgo
    Auf GitHub ansehen↗4,460
  • jodydonetti/ziggycreatures.fusioncacheAvatar von jodydonetti

    jodydonetti/ZiggyCreatures.FusionCache

    3,784Auf GitHub ansehen↗

    FusionCache is a hybrid distributed caching library that coordinates local memory and distributed storage to balance access speed with global consistency. It functions as a resilient data access layer, utilizing a pluggable serialization framework to convert cached objects into various binary or text formats for compatibility across diverse storage environments. The system maintains cluster consistency through a distributed cache synchronizer that propagates invalidations and state updates across multiple nodes via a shared messaging backplane. It improves reliability by serving stale cache d

    Propagates cache updates and invalidations across multiple application instances via a shared messaging backplane.

    C#
    Auf GitHub ansehen↗3,784
  • ziggycreatures/fusioncacheAvatar von ZiggyCreatures

    ZiggyCreatures/FusionCache

    3,543Auf GitHub ansehen↗

    FusionCache is a .NET caching framework that manages local and distributed data storage. It functions as a hybrid cache implementation, combining fast in-memory storage with a distributed second-level cache to reduce latency and remote data fetches. The framework includes a cache stampede protector that ensures only one request fetches missing data while concurrent calls wait. It synchronizes data across multiple application nodes using a backplane and provides an observability-driven approach with built-in metrics, structured logging, and telemetry. The system covers a broad range of cachin

    Uses a backplane to notify multiple application nodes of cache changes for data consistency.

    C#asynccachecache-stampede
    Auf GitHub ansehen↗3,543
  • ever-co/ever-gauzyAvatar von ever-co

    ever-co/ever-gauzy

    3,476Auf GitHub ansehen↗

    Ever Gauzy is an integrated business management suite providing an ERP and CRM framework for professional services automation. It functions as a multi-tenant SaaS platform that combines time tracking, billing, and human resource management into a unified system. The project is distinguished by its headless architecture, utilizing a REST and GraphQL API gateway to expose business operations. It features a Model Context Protocol server that allows AI assistants to interact with system data and execute functional tools for automated business workflows. The platform covers a broad operational su

    Synchronizes cache and session data across multiple server instances using a remote store.

    TypeScriptaccountingbillingbookkeeping
    Auf GitHub ansehen↗3,476
  • discourse/message_busAvatar von discourse

    discourse/message_bus

    1,663Auf GitHub ansehen↗

    Message Bus is a messaging library for Ruby and Rack applications designed to facilitate real-time data broadcasting and inter-process communication. It provides a framework for pushing live updates to connected clients and synchronizing state across multiple application instances, ensuring consistent data delivery in scaled environments. The library distinguishes itself through a flexible architecture that supports multiple storage backends, including Redis, PostgreSQL, and in-memory options. It functions as a persistent connection framework that serves as an alternative to traditional web s

    Propagates cache invalidations across multiple application instances to maintain consistency in scaled environments.

    Rubyrubygem
    Auf GitHub ansehen↗1,663
  • tompave/fun_with_flagsAvatar von tompave

    tompave/fun_with_flags

    1,160Auf GitHub ansehen↗

    This project is a feature flag library for Elixir applications, designed to manage and toggle application functionality at runtime. It provides a distributed system for controlling code paths without requiring new deployments, allowing developers to enable or disable features globally, for specific users, or for defined groups. The library distinguishes itself through a pluggable persistence framework that supports various storage backends, ensuring that flag configurations remain consistent across application restarts. It maintains state synchronization across distributed nodes using messagi

    Synchronizes cache states across distributed application nodes using messaging backends to ensure consistent configuration.

    Elixirectoelixirfeature-flags
    Auf GitHub ansehen↗1,160
  1. Home
  2. Data & Databases
  3. Distributed State Synchronizers
  4. Distributed Cache Synchronizers

Unter-Tags erkunden

  • Local Cache SynchronizationEnsures consistency between the in-memory object cache and the underlying database after modifications. **Distinct from Distributed Cache Synchronizers:** Focuses on local memory state consistency for the ORM, unlike distributed cache synchronizers that use network backplanes
  • Transactional Cache Updates1 Sub-TagMechanisms for atomically updating a database and asynchronously updating a cache to ensure eventual consistency. **Distinct from Distributed Cache Synchronizers:** More specific than Distributed Cache Synchronizers: specifically uses a two-phase message pattern for database-to-cache consistency.