How does Cassandra achieve high availability?
Some of the ways in which Cassandra achieves high availability include the following:
- Distributed architecture: Cassandra utilizes a distributed architecture where data is spread across multiple nodes, with each node containing a full copy of the data. This ensures that even if one node fails, the other nodes can still provide data services.
- Data Replication: Cassandra ensures high availability of data through its data replication mechanism. Each data replica is copied to multiple nodes, so even if a node fails, data can still be retrieved from other nodes.
- Automated fault detection and recovery: Cassandra can automatically detect if a node is down, and carry out the necessary fault handling and data recovery. If a node goes down, Cassandra will automatically restore data replicas to other nodes, ensuring data availability.
- Decentralized architecture: Cassandra operates without a central point of failure, as all nodes are equal and there is no centralized control node. This means that even if one node fails, the other nodes can still provide service without affecting the overall system availability.
- Data sharding and load balancing: Cassandra can partition data storage across different nodes and evenly distribute requests to different nodes through a load balancing mechanism, ensuring the stability and scalability of the system.
Overall, Cassandra achieves high availability through various methods such as distributed architecture, data replication, automatic fault detection and recovery, decentralized architecture, and data sharding and load balancing to ensure data reliability and system stability.