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5 रिपॉजिटरी

Awesome GitHub RepositoriesDistributed State Persistence

Solutions for maintaining shared state across multiple independent application instances.

Distinguishing note: Focuses on distributed state synchronization rather than local persistence.

Explore 5 awesome GitHub repositories matching data & databases · Distributed State Persistence. Refine with filters or upvote what's useful.

Awesome Distributed State Persistence GitHub Repositories

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

    gocolly/colly

    25,101GitHub पर देखें↗

    Colly is a high-performance web scraping framework designed for the automated extraction of structured data from websites. It provides a programmable toolkit that manages the complexities of large-scale data collection, including concurrent request orchestration, automatic cookie handling, and robots.txt compliance. By utilizing an asynchronous execution model, the engine maintains high throughput while preventing resource exhaustion during recursive or distributed crawling tasks. The framework is distinguished by its modular, event-driven architecture, which allows developers to hook into sp

    Maintains shared cookie and URL history state across multiple independent instances in distributed environments.

    Gocrawlercrawlingframework
    GitHub पर देखें↗25,101
  • optuna/optunaoptuna का अवतार

    optuna/optuna

    14,388GitHub पर देखें↗

    Optuna is a Python-based hyperparameter optimization framework designed to automate the search for optimal machine learning model configurations. It functions as a Bayesian optimization library that systematically tests parameter combinations to maximize or minimize objective functions, streamlining the model development process through iterative evaluation. The project distinguishes itself through a define-by-run dynamic construction model, which allows users to build complex, conditional search spaces using standard programming logic. Its architecture is highly modular, featuring a pluggabl

    Maintains study results and trial history across distributed environments and sessions.

    Pythondistributedhyperparameter-optimizationmachine-learning
    GitHub पर देखें↗14,388
  • dotnet/orleansdotnet का अवतार

    dotnet/orleans

    10,789GitHub पर देखें↗

    Orleans is a .NET distributed actor framework designed for building scalable, cloud-native applications. It implements a virtual actor model where entities with stable identities manage their own state and lifecycle across a cluster of servers. The framework provides a distributed state management system with ACID transaction support and a distributed pub/sub streaming engine for real-time data processing. It distinguishes itself through location-transparent routing, automatic actor activation and deactivation, and elastic cluster scaling that redistributes workloads during node failures. Th

    Persists actor-specific state to external storage to ensure durability and recovery across node failures.

    C#actor-modelactorscloud-computing
    GitHub पर देखें↗10,789
  • apache/openwhiskapache का अवतार

    apache/openwhisk

    6,779GitHub पर देखें↗

    OpenWhisk is a serverless cloud platform designed for deploying and executing stateless functions in response to API calls or events. It serves as a complete serverless stack, providing an API gateway for functions, a function-as-a-service runtime manager, and an event-driven workflow engine. The platform distinguishes itself through a polyglot execution model that supports multiple language runtimes and allows for the creation of custom runtimes using Docker containers. It enables complex logic through function orchestration and composition, allowing multiple functions to be chained into seq

    Utilizes a distributed document database like CouchDB to persist user configurations, action definitions, and system metadata.

    Scala
    GitHub पर देखें↗6,779
  • hazelcast/hazelcasthazelcast का अवतार

    hazelcast/hazelcast

    6,570GitHub पर देखें↗

    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

    Saves consensus subsystem data to stable storage to ensure that committed operations are recovered automatically following crashes.

    Javabig-datacachingdata-in-motion
    GitHub पर देखें↗6,570
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  3. Distributed State Persistence

सब-टैग एक्सप्लोर करें

  • Processor State SnapshotsPersistence of internal processor state to distributed maps during snapshot barriers. **Distinct from Distributed State Persistence:** Distinct from Distributed State Persistence: focuses on stream processor state snapshots for fault tolerance rather than general application state.