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Lecture

Eventual Consistency: NoSQL, CAP Theorem, and BASE

In course

CS-422: Database systems

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and und ...

Description

This lecture covers the concept of eventual consistency in distributed systems, exploring how NoSQL databases handle failures and replication. It delves into the CAP theorem, which highlights the trade-offs between Consistency, Availability, and Partition Tolerance. The instructor explains the transition from ACID properties to BASE principles, emphasizing the importance of soft state and eventual consistency. Various strategies for tracking mutable, replicated state are discussed, including synchronous and asynchronous replication, read and write quorums, and setting parameters for fast response times. The lecture also touches on the challenges of ensuring strong consistency in distributed systems and the implications of different quorum settings on system performance.

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Instructor

Anastasia Ailamaki

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Related concepts (32)

Replication (computing)

Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility. Replication in computing can refer to: Data replication, where the same data is stored on multiple storage devices Computation replication, where the same computing task is executed many times.

Consistency model

In computer science, a consistency model specifies a contract between the programmer and a system, wherein the system guarantees that if the programmer follows the rules for operations on memory, memory will be consistent and the results of reading, writing, or updating memory will be predictable. Consistency models are used in distributed systems like distributed shared memory systems or distributed data stores (such as s, databases, optimistic replication systems or web caching).

CAP theorem

In theoretical computer science, the CAP theorem, also named Brewer's theorem after computer scientist Eric Brewer, states that any distributed data store can provide only two of the following three guarantees: Consistency Every read receives the most recent write or an error. Availability Every request receives a (non-error) response, without the guarantee that it contains the most recent write. Partition tolerance The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes.

NoSQL

A NoSQL (originally referring to "non-SQL" or "non-relational") database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Such databases have existed since the late 1960s, but the name "NoSQL" was only coined in the early 21st century, triggered by the needs of Web 2.0 companies. NoSQL databases are increasingly used in big data and real-time web applications.

Disk mirroring

In data storage, disk mirroring is the replication of logical disk volumes onto separate physical hard disks in real time to ensure continuous availability. It is most commonly used in RAID 1. A mirrored volume is a complete logical representation of separate volume copies. In a disaster recovery context, mirroring data over long distance is referred to as storage replication. Depending on the technologies used, replication can be performed synchronously, asynchronously, semi-synchronously, or point-in-time.

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