#MONGODB VS POSTGRESQL SOFTWARE#

This theorem is further used to loosely classify databases into three families, CA, CP, and AP. The CAP theorem states that a networked shared-data system can have at most two of the following three guarantees: consistency (at any given point, every node sees the same data, and the data is up to date) availability (every request is correctly notified by every node), partition tolerance (The system functions irrespective of network partitioning). 1.1 The CAP theorem.Īny serious discussion of databases will include at least passing reference to the CAP theorem. Everything discussed here, will be assumed as background knowledge throughout the rest of this article. In this chapter we will talk about the theoretical background necessary for a serious discussion of databases. The second chapter will compare, at a high level, the features provided by both databases, and attempt to resolve this battle once and for all! In the interests of continuing the whimsy, when a round ends with a clearly dominant winner, I will declare it by knockout, but when it is slightly less clear cut, I will call it a technical decision, and include some justification. If you already have a solid understanding of database theory, the first chapter can be skipped with no loss of information. Knowledge of databases is not required, as background theory will be explained. Some understanding of JSON would be advantageous. This article is going to assume a relatively high level of general technical ability.

Entire families are not represented (graph databases for one). It is by no means a comprehensive survey of the database landscape. It will look at the strengths and weaknesses of both, and try to make practical recommendations for when to use which. This article will compare and contrast one of the most commonly used relational databases (Postgres) with one of the most commonly used document databases (Mongo).

#MONGODB VS POSTGRESQL SOFTWARE#

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Mongodb vs postgresql