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Understanding the CAP theorem

From: Up and Running with NoSQL Databases

Video: Understanding the CAP theorem

Finding the ideal database for your application is largely a choice between trade-offs. The CAP theorem is one concept that can help you understand the trade-offs between different databases. The CAP theorem was originally proposed by Eric Brewer in 2000. It was originally conceptualized around network shared data and is often used to generalize the tradeoffs between different databases. The CAP theorem centers around three desirable properties; consistency is where all users get the same data, no matter where they read the data from, availability ensures users can always read from and write to the database, and finally partition tolerance ensures that the database works when divided across network.

Understanding the CAP theorem

Finding the ideal database for your application is largely a choice between trade-offs. The CAP theorem is one concept that can help you understand the trade-offs between different databases. The CAP theorem was originally proposed by Eric Brewer in 2000. It was originally conceptualized around network shared data and is often used to generalize the tradeoffs between different databases. The CAP theorem centers around three desirable properties; consistency is where all users get the same data, no matter where they read the data from, availability ensures users can always read from and write to the database, and finally partition tolerance ensures that the database works when divided across network.

The theorem states that at most you can only guarantee two of the three properties simultaneously. So you can have an available partition- tolerant database, a consistent partition-tolerant database or a consistent available database. One thing to note is that not all of these properties are necessarily exclusive of each other. You can have a consistent partition-tolerant database that still has an emphasis on availability, but you're going to sacrifice either part of your consistency or your partition tolerance.

Relational databases trend towards consistency and availability. Partition tolerance is something that relational databases typically don't handle very well. Often you have to write custom code to handle the partitioning of relational databases. NoSQL databases on the other hand trend towards partition-tolerance. They are designed with the idea in mind that you're going to be adding more nodes to your database as it grows. CouchDB, which we looked at earlier in the course, is an available partition-tolerant database.

That means the data is always available to read from and write to, and that you're able to add partitions as your database grows. In some instances, the CAP theorem may not apply to your application. Depending on the size of your application, CAP tradeoffs may be irrelevant. If you have a small or a low traffic website, partitions may be useless to you, and in some cases consistency tradeoffs may not be noticeable. For instance, the votes on a comment may not show up right away for all users.

This is fine as long as all votes are displayed eventually. The CAP theorem can be used as a guide for categorizing the tradeoffs between different databases. Consistency, availability, and partition tolerance are all desirable properties in a database. While you may not be able to get all three in any single database system, you can use the CAP theorem to help you decide what to prioritize.

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Up and Running with NoSQL Databases

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