Leaderless replication decentralizes data writes, allowing any replica to accept them. Examples include Amazon's Dynamo and open-source platforms like Riak and Cassandra. Mechanisms like read repair and anti-entropy ensure eventual consistency.
This blog explores multi-leader replication in distributed systems, highlighting its advantages and challenges. Approach with caution.
This blog explains single leader replication, synchronous/asynchronous replication, setting up new followers, handling node outages, and ensuring read consistency in distributed systems.
Partitioning is the process of splitting a large database into smaller, more manageable parts called partitions.
"Handling Write Conflicts in Collaborative Editing" explores strategies and techniques for efficient conflict handling in distributed databases.
Quorums are the minimum number of votes required for the read or write to be valid. In distributed systems, quorums are used to ensure consistency and availability. This post explains how quorums are used in distributed systems.
Transactions group database operations into atomic units ensuring consistency and isolation. Safely handling errors and aborts requires deduplication, backoff, separating transient errors, and managing external side effects to avoid data loss or duplication.
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