📜  传统数据与大数据的区别

📅  最后修改于: 2021-09-12 10:49:57             🧑  作者: Mango

1. 传统数据:
传统数据是结构化数据,主要由从小到大的所有类型的企业维护。在传统数据库系统中,一种集中式数据库架构,用于以固定格式或文件中的字段存储和维护数据。使用结构化查询语言 (SQL) 来管理和访问数据。

2. 大数据:
我们可以将大数据视为传统数据的上层版本。大数据处理过大或复杂的数据集,传统数据处理应用软件难以管理。它处理大量结构化、半结构化和非结构化数据。 Volume、Velocity 和 Variety、Veracity 和 Value 是指大数据的 5’V 特征。大数据不仅是指大量的数据,它是指通过分析海量复杂的数据集,提取出有意义的数据。

传统数据与大数据的区别:

S.No. TRADITIONAL DATA BIG DATA
01. Traditional data is generated in enterprise level. Big data is generated in outside and enterprise level.
02. Its volume ranges from Gigabytes to Terabytes. Its volume ranges from Petabytes to Zettabytes or Exabytes.
03. Traditional database system deals with structured data. Big data system deals with structured, semi structured and unstructured data.
04. Traditional data is generated per hour or per day or more. But big data is generated more frequently mainly per seconds.
05. Traditional data source is centralized and it is managed in centralized form. Big data source is distributed and it is managed in distributed form.
06. Data integration is very easy. Data integration is very difficult.
07. Normal system configuration is capable to process traditional data. High system configuration is required to process big data.
08. The size of the data is very small. The size is more than the traditional data size.
09. Traditional data base tools are required to perform any data base operation. Special kind of data base tools are required to perform any data base operation.
10. Normal functions can manipulate data. Special kind of functions can manipulate data.
11. Its data model is strict schema based and it is static. Its data model is flat schema based and it is dynamic.
12.. Traditional data is stable and inter relationship. Big data is not stable and unknown relationship.
13. Traditional data is in manageable volume. Big data is in huge volume which becomes unmanageable.
14. It is easy to manage and manipulate the data. It is difficult to manage and manipulate the data.
15. Its data sources includes ERP transaction data, CRM transaction data, financial data, organizational data, web transaction data etc. Its data sources includes social media, device data, sensor data, video, images, audio etc.