DBMS中面向行和面向列的数据存储之间的区别

数据存储基本上是用于存储数据集合的地方，例如数据库、文件系统或目录。在数据库系统中，它们可以通过两种方式存储。这些如下：

1. 面向行的数据存储
2. 面向列的数据存储

面向行的数据存储和面向列的数据存储的比较如下：

Row oriented data stores	Column oriented data stores
Data is stored and retrieved one row at a time and hence could read unnecessary data if some of the data in a row are required.	In this type of data stores, data are stored and retrieve in columns and hence it can only able to read only the relevant data if required.
Records in Row Oriented Data stores are easy to read and write.	In this type of data stores, read and write operations are slower as compared to row-oriented.
Row-oriented data stores are best suited for online transaction system.	Column-oriented stores are best suited for online analytical processing.
These are not efficient in performing operations applicable to the entire datasets and hence aggregation in row-oriented is an expensive job or operations.	These are efficient in performing operations applicable to the entire dataset and hence enables aggregation over many rows and columns.
Typical compression mechanisms which provide less efficient result than what we achieve from column-oriented data stores.	These type of data stores basically permits high compression rates due to little distinct or unique values in columns.

面向行的数据存储的最佳示例是关系数据库，它是一种结构化数据存储，也是一个复杂的查询引擎。随着数据大小的增加，提高性能会带来很大的损失。

面向列的数据存储的最佳示例是HBase 数据库，它基本上是从头开始设计的，旨在提供可扩展性和分区，以实现高效的数据结构序列化、存储和检索。

关系型数据库和 HBase 的特点如下：

Relational Database	HBase
It is basically based on a Fixed Schema.	It is totally Schema-less.
It is an example of row-oriented datastore.	It is an example of column-oriented datastores.
It is basically designed to store normalized data.	It is basically designed to store de-normalized data.
It basically contains thin tables.	It basically contains wide and sparsely oriented populated tables.
It has no built-in support for partitioning.	It basically supports Automatic Partitioning.