The best way to learn new concepts is to know the 5Ws and H, but with this topic, not all of these are applicable so by the end of this blog you will know:

学习新概念的最佳方法是了解5W和H，但是对于本主题，并非所有这些都适用，因此在本博客结尾时，您将知道：

1. What is a schema?什么是架构？
2. How are schema and schemaless databases different?模式数据库和无模式数据库有何不同？
3. Why is each beneficial?为什么每个都有好处？

什么是模式，这对数据意味着什么？ (What is a schema and what does that mean for the data?)

A schema is the structure of a database and it encapsulates things such as tables and columns. It allows for normalization and regulation of the data being entered into the database.

模式是数据库的结构，它封装了诸如表和列之类的东西。 它允许对输入数据库的数据进行规范化和规范化。

So a schemaless database not having a schema allows for data to be entered in any manner the developer finds to be necessary but documents in the same collection closely resemble each other configurations.

因此，没有模式的无模式数据库允许以开发人员认为必要的任何方式输入数据，但是同一集合中的文档彼此非常相似。

它们有何不同？ (How are they different?)

The first is that schema databases are written in SQL while schemaless databases are written in a NoSQL language (like MongoDB) and utilize JSON documents or key/value pairs. The second difference is that they are used in different types of databases: schemas are for relational databases while schemaless databases are non-relational. A relational database relies on the schemas outline, tables and columns so that relations can be set between tables.

首先是模式数据库是用SQL编写的，而无模式数据库是用NoSQL语言(如MongoDB)编写的，并利用JSON文档或键/值对。 第二个区别是它们在不同类型的数据库中使用：模式用于关系数据库，而无模式数据库是非关系数据库。 关系数据库依赖于架构大纲，表和列，以便可以在表之间设置关系。

This causes components of data entries to be separated and placed into their proper table. For example in the first table pictured above the author went to the authors table while the book went to the books table. But in the second picture, we see how a non-relational database instead keeps the entry together.

这导致数据条目的组件被分离并放置在其适当的表中。 例如，在笔者上图中第一台去了authors表，而这本书去了books表。 但是在第二张图中，我们看到了非关系数据库如何将条目保持在一起。

为什么每个都有好处？ (Why are each beneficial?)

Because of their horizontal scalability, schemaless database scale almost effortlessly. To change the standard of data entry no work is needed. As seen above, only the last entry has an amt property. To do that, I didn’t have to add a column, all that I did was add the property to the JSON document. In a schema database, I at least have to add a column. And if I were to ignore a column that had a NOT NULL constraint, a schema database would not add that entry at all. I would have to alter the entire table to remove the column.

由于其水平可伸缩性，无模式数据库几乎可以轻松扩展。 要更改数据输入的标准，无需任何工作。 如上所示，只有最后一个条目具有amt属性。 为此，我不必添加列，只需将属性添加到JSON文档即可。 在模式数据库中，我至少必须添加一列。 而且，如果我忽略具有NOT NULL约束的列，则模式数据库根本不会添加该条目。 我将不得不更改整个表以删除该列。

A schema database allows for the utmost clarity. The data is consistent and with constraints, you know exactly what you’ll be receiving such as whether it’s an integer or characters. The relationships between tables are also clear cut due to foreign and primary keys.

模式数据库可提供最大的清晰度。 数据是一致的并且有约束，您确切地知道将要接收的内容，例如它是整数还是字符。 由于外键和主键，表之间的关系也很清晰。