Optimizing Read Performance in Distributed Key-Value Stores Using Serializable Consistency
Author(s): Naveen Srikanth Pasupuleti
Publication #: 2505045
Date of Publication: 11.06.2024
Country: USA
Pages: 1-20
Published In: Volume 10 Issue 3 June-2024
Abstract
ETCD is a distributed key-value store designed to manage critical configuration data, service discovery, and coordination information in distributed systems, offering high availability, fault tolerance, and strong consistency through the Raft consensus protocol. This protocol ensures that all nodes in the cluster maintain the same data view, even in the presence of network failures or node crashes. In etcd, read operations can be categorized into linearizable and serializable reads. Linearizable reads provide the highest level of consistency, ensuring that the client retrieves the most recent data that has been acknowledged by the Raft leader node, which is crucial for tasks like leader election, distributed locking, and configuration management. However, linearizable reads tend to introduce higher latency due to the additional communication and synchronization required. On the other hand, serializable reads offer a faster alternative with lower latency, as they do not require synchronization with the leader node. These reads ensure consistency within a certain scope but may return slightly stale data, making them suitable for use cases where absolute real-time consistency is not necessary. The flexibility of choosing between linearizable and serializable reads allows etcd to cater to different application needs, balancing consistency and performance depending on the specific requirements of the system. Linearizable reads guarantee strong consistency but may incur higher latency, while serializable reads provide a more efficient solution with a weaker consistency model. This adaptability makes etcd a reliable and scalable choice for managing configuration data and coordinating distributed systems in various cloud-native environments. This flexibility in read operations ensures that distributed systems can make trade-offs between performance and consistency based on the specific needs of their use cases. In scenarios where real-time consistency is paramount, linearizable reads are the ideal choice, as they guarantee the most up-to-date data. However, in situations where performance is prioritized and some level of staleness is acceptable, serializable reads offer a more efficient solution. The combination of both read models enables etcd to serve a wide range of applications, from real-time coordination tasks to high-performance configurations. By offering both consistency and performance options, etcd meets the demands of modern distributed systems. Linearizable read operations are having performance issues. This paper addresses this issue using serializable read operations.
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