📜  RDBMS 和 Hadoop 的区别

📅  最后修改于: 2021-10-19 04:36:13             🧑  作者: Mango

RDMS(Relational Database Management System): RDBMS 是一种信息管理系统,它基于一种数据模型。在 RDBMS 中,表用于信息存储。表的每一行代表一条记录,列代表数据的一个属性。 RDBMS 中的数据组织及其操作过程与其他数据库不同。 RDBMS 确保设计数据库所需的 ACID(原子性、一致性、完整性、持久性)属性。 RDBMS 的目的是尽可能快速可靠地存储、管理和检索数据。

Hadoop:它是一种开源软件框架,用于在一组商品硬件上存储数据和运行应用程序。它具有大存储容量和高处理能力。它可以同时管理多个并发进程。它用于预测分析、数据挖掘和机器学习。它可以处理结构化和非结构化形式的数据。与传统的 RDBMS 相比,它在存储、处理和管理数据方面更加灵活。与传统系统不同,Hadoop 支持同时对同一数据进行多个分析过程。它非常灵活地支持可扩展性。

下表列出了数据科学和数据可视化之间的差异:

S.No. RDBMS Hadoop
1. Traditional row-column based databases, basically used for data storage, manipulation and retrieval. An open-source software used for storing data and running applications or processes concurrently.
2. In this structured data is mostly processed. In this both structured and unstructured data is processed.
3. It is best suited for OLTP environment. It is best suited for BIG data.
4. It is less scalable than Hadoop. It is highly scalable.
5. Data normalization is required in RDBMS. Data normalization is not required in Hadoop.
6. It stores transformed and aggregated data. It stores huge volume of data.
7. It has no latency in response. It has some latency in response.
8. The data schema of RDBMS is static type. The data schema of Hadoop is dynamic type.
9. High data integrity available. Low data integrity available than RDBMS.
10. Cost is applicable for licensed software. Free of cost, as it is an open source software.