# The CAP theorem series

DevFeed: [The CAP theorem series](<https://devfeed.tech/articles/the-cap-theorem-series-21686.md>)

Original publisher: [Read original article](<http://blog.thislongrun.com/2015/03/the-cap-theorem-series.html>)

Author: Nicolas Liochon (noreply@blogger.com)

Published: 2015-03-10T15:10:00Z

Content type: article

Language: en

Sources: [Nicolas Liochon](<https://devfeed.tech/sources/nicolas-liochon.md>)

Topics: [distributed-systems](<https://devfeed.tech/topics/distributed-systems.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Availability](<https://devfeed.tech/topics/availability.md>), [big-data](<https://devfeed.tech/topics/big-data.md>)

Tags: [acid](<https://devfeed.tech/tags/acid.md>), [availability](<https://devfeed.tech/tags/availability.md>), [big-data](<https://devfeed.tech/tags/big-data.md>), [cap-theorem](<https://devfeed.tech/tags/cap-theorem.md>), [consistency](<https://devfeed.tech/tags/consistency.md>), [database](<https://devfeed.tech/tags/database.md>), [databases](<https://devfeed.tech/tags/databases.md>), [distributed-system](<https://devfeed.tech/tags/distributed-system.md>), [distributed-systems](<https://devfeed.tech/tags/distributed-systems.md>), [durability](<https://devfeed.tech/tags/durability.md>), [latency](<https://devfeed.tech/tags/latency.md>), [network](<https://devfeed.tech/tags/network.md>), [partition](<https://devfeed.tech/tags/partition.md>)

## AI overview

An introduction to a series examining the CAP theorem and databases. The series addresses commonly misunderstood distinctions involving consistency, availability, partitions, node failures, packet loss, ACID terminology, and distributed-system categories.

## Source excerpt

Let me introduce a new series of posts on the CAP theorem. CAP is a well known theorem conjectured and proven by recognized researchers in distributed systems, namely Eric Brewer, Seth Gilbert and Nancy Lynch. It is also widely used to categorize distributed applications. With CAP, do computer scientists actually have a better classification tool than biologists? Why you want to read this series on CAP theorem and databases This series covers some points often forgotten or misunderstood and sometimes never mentioned, such as: '42' is not a valid answer for an eventually consistent database; Node failures and packet loss are not partitions; Consistent in ACID and Consistent in CAP are two different things; The CAP definition of availability is key but very different from what most people think; There are some systems that do not fit into the three CA/CP/CA categories; It's possible to use the CA category, really possible, There is no such thing as an eventually consistent and available big data database. The posts, in recommended reading order Comparing Eventually Consistent and CP-as-in-CAP stores: Introduces the definitions of "Consistent" and "Available" in the CAP theorem. By comparing them with the definition of "Eventual Consistency" we show the limits of these definitions. The confusing ACID and CAP wording: Explains the terminologies of ACID and CAP, and how they overlap. Covers as well the difference between the theoretical definition of the 'I' in ACID and its actual implementation with multiple "isolation degrees". It's a good starting point if you know the "Consistency" definition of ACID but not the "Consistency" definition of CAP. Don't use the CAP theorem for node failures: Looks at a common misunderstanding of the CAP theorem: node failures are not partitions. It's also a pretext to look at the actual proof of CAP, and to go into the definition of "Partition" in CAP. Don't use the CAP theorem for packet losses: Looks at another common misunderstanding