所有应用软件之中，数据库可能是最复杂的。

MySQL的手册有3000多页，PostgreSQL的手册有2000多页，Oracle的手册更是比它们相加还要厚。

但是，自己写一个最简单的数据库，做起来并不难。Reddit上面有一个帖子，只用了几百个字，就把原理讲清楚了。下面是我根据这个帖子整理的内容。

一、数据以文本形式保存

第一步，就是将所要保存的数据，写入文本文件。这个文本文件就是你的数据库。

为了方便读取，数据必须分成记录，每一条记录的长度规定为等长。比如，假定每条记录的长度是800字节，那么第5条记录的开始位置就在3200字节。

大多数时候，我们不知道某一条记录在第几个位置，只知道主键（primary key）的值。这时为了读取数据，可以一条条比对记录。但是这样做效率太低，实际应用中，数据库往往采用B树（B-tree）格式储存数据。

二、什么是B树？

要理解B树，必须从二叉查找树（Binary search tree）讲起。

二叉查找树是一种查找效率非常高的数据结构，它有三个特点。

（1）每个节点最多只有两个子树。

（2）左子树都为小于父节点的值，右子树都为大于父节点的值。

（3）在n个节点中找到目标值，一般只需要log(n)次比较。

二叉查找树的结构不适合数据库，因为它的查找效率与层数相关。越处在下层的数据，就需要越多次比较。极端情况下，n个数据需要n次比较才能找到目标值。对于数据库来说，每进入一层，就要从硬盘读取一次数据，这非常致命，因为硬盘的读取时间远远大于数据处理时间，数据库读取硬盘的次数越少越好。

B树是对二叉查找树的改进。它的设计思想是，将相关数据尽量集中在一起，以便一次读取多个数据，减少硬盘操作次数。

B树的特点也有三个。

（1）一个节点可以容纳多个值。比如上图中，最多的一个节点容纳了4个值。

（2）除非数据已经填满，否则不会增加新的层。也就是说，B树追求"层"越少越好。

（3）子节点中的值，与父节点中的值，有严格的大小对应关系。一般来说，如果父节点有a个值，那么就有a+1个子节点。比如上图中，父节点有两个值（7和16），就对应三个子节点，第一个子节点都是小于7的值，最后一个子节点都是大于16的值，中间的子节点就是7和16之间的值。

这种数据结构，非常有利于减少读取硬盘的次数。假定一个节点可以容纳100个值，那么3层的B树可以容纳100万个数据，如果换成二叉查找树，则需要20层！假定操作系统一次读取一个节点，并且根节点保留在内存中，那么B树在100万个数据中查找目标值，只需要读取两次硬盘。

三、索引

数据库以B树格式储存，只解决了按照"主键"查找数据的问题。如果想查找其他字段，就需要建立索引（index）。

所谓索引，就是以某个字段为关键字的B树文件。假定有一张"雇员表"，包含了员工号（主键）和姓名两个字段。可以对姓名建立索引文件，该文件以B树格式对姓名进行储存，每个姓名后面是其在数据库中的位置（即第几条记录）。查找姓名的时候，先从索引中找到对应第几条记录，然后再从表格中读取。

这种索引查找方法，叫做"索引顺序存取方法"（Indexed Sequential Access Method），缩写为ISAM。它已经有多种实现（比如C-ISAM库和D-ISAM库），只要使用这些代码库，就能自己写一个最简单的数据库。

四、高级功能

部署了最基本的数据存取（包括索引）以后，还可以实现一些高级功能。

（1）SQL语言是数据库通用操作语言，所以需要一个SQL解析器，将SQL命令解析为对应的ISAM操作。

（2）数据库连接（join）是指数据库的两张表通过"外键"，建立连接关系。你需要对这种操作进行优化。

（3）数据库事务（transaction）是指批量进行一系列数据库操作，只要有一步不成功，整个操作都不成功。所以需要有一个"操作日志"，以便失败时对操作进行回滚。

（4）备份机制：保存数据库的副本。

（5）远程操作：使得用户可以在不同的机器上，通过TCP/IP协议操作数据库。

（完）

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How do you build a database? self.Database

Its a great question, and deserves a long answer.

Most database servers are built in C, and store data using B-tree type constructs. In the old days there was a product called C-Isam (c library for an indexed sequential access method) which is a low level library to help C programmers write data in B-tree format. So you need to know about btrees and understand what these are.

Most databases store data separate to indexes. Lets assume a record (or row) is 800 bytes long and you write 5 rows of data to a file. If the row contains columns such as first name, last name, address etc. and you want to search for a specific record by last name, you can open the file and sequentially search through each record but this is very slow. Instead you open an index file which just contains the lastname and the position of the record in the data file. Then when you have the position you open the data file, lseek to that position and read the data. Because index data is very small it is much quicker to search through index files. Also as the index files are stored in btrees in it very quick to effectively do a quicksearch (divide and conquer) to find the record you are looking for.

So you understand for one "table" you will have a data file with the data and one (or many) index files. The first index file could be for lastname, the next could be to search by SS number etc. When the user defines their query to get some data, they decide which index file to search through. If you can find any info on C-ISAM (there used to be an open source version (or cheap commercial) called D-ISAM) you will understand this concept quite well.

Once you have stored data and have index files, using an ISAM type approach allows you to GET a record based on a value, or PUT a new record. However modern database servers all support SQL, so you need an SQL parser that translates the SQL statement into a sequence of related GETs. SQL may join 2 tables so an optimizer is also needed to decide which table to read first (normally based on number of rows in each table and indexes available) and how to relate it to the next table. SQL can INSERT data so you need to parse that into PUT statements but it can also combine multiple INSERTS into transactions so you need a transaction manager to control this, and you will need transaction logs to store wip/completed transactions.

It is possible you will need some backup/restore commands to backup your data files and index files and maybe also your transaction log files, and if you really want to go for it you could write some replication tools to read your transaction log and replicate the transactions to a backup database on a different server. Note if you want your client programs (for example an SQL UI like phpmyadmin) to reside on separate machine than your database server you will need to write a connection manager that sends the SQL requests over TCP/IP to your server, then authenticate it using some credentials, parse the request, run your GETS and send back the data to the client.

So these database servers can be a lot of work, especially for one person. But you can create simple versions of these tools one at a time. Start with how to store data and indexes, and how to retrieve data using an ISAM type interface.

There are books out there - look for older books on mysql and msql, look for anything on google re btrees and isam, look for open source C libraries that already do isam. Get a good understanding on file IO on a linux machine using C. Many commercial databases now dont even use the filesystem for their data files because of cacheing issues - they write directly to raw disk. You want to just write to files initially.

I hope this helps a little bit.