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2 Repos

Awesome GitHub RepositoriesReplication Mode Configurators

Utilities for switching between different data synchronization modes such as synchronous and asynchronous.

Distinguishing note: Existing candidates focus on memory safety or rendering modes, not database replication modes

Explore 2 awesome GitHub repositories matching data & databases · Replication Mode Configurators. Refine with filters or upvote what's useful.

Awesome Replication Mode Configurators GitHub Repositories

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  • patroni/patroniAvatar von patroni

    patroni/patroni

    8,182Auf GitHub ansehen↗

    Patroni is a high availability manager and cluster orchestrator for PostgreSQL. It functions as an automatic failover controller and replication manager that ensures continuous database availability by automating leader election and promoting standby nodes during failures. The system maintains a consistent cluster state by acting as a distributed consensus coordinator. It synchronizes configuration and manages leader elections through integration with distributed configuration stores such as etcd, ZooKeeper, or Consul. Its broader capabilities include managing both synchronous and asynchrono

    Provides the ability to toggle between synchronous and asynchronous replication modes to balance durability and latency.

    Pythonconsuletcdfailover
    Auf GitHub ansehen↗8,182
  • hazelcast/hazelcastAvatar von hazelcast

    hazelcast/hazelcast

    6,570Auf GitHub ansehen↗

    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

    Controls data durability by choosing between synchronous or asynchronous replication modes to balance latency against safety.

    Javabig-datacachingdata-in-motion
    Auf GitHub ansehen↗6,570
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