📜  大数据与云计算的区别

📅  最后修改于: 2021-09-14 02:38:19             🧑  作者: Mango

1.大数据
大数据是指规模庞大且随时间增长迅速的数据。大数据包括结构化数据、非结构化数据和半结构化数据。传统的数据管理工具无法对大数据进行存储和处理,需要专门的大数据管理工具。它是指具有 5 V 的体积、速度、真实性、价值和多样性信息资产的复杂和大型数据集。它包括数据存储、数据分析、数据挖掘和数据可视化。

生成大数据的来源示例包括社交媒体数据、电子商务数据、气象站数据、物联网传感器数据等。

大数据的特点:

  • 各种大数据——结构化、非结构化和半结构化数据
  • 大数据的速度——数据生成的速度
  • 大数据量——正在生成的海量数据
  • 大数据的价值——提取有用的信息并使其有价值
  • 大数据的可变性——数据有时会显示出不一致。

大数据的优势:

  • 节约成本
  • 更好的决策
  • 更好的销售洞察
  • 提高生产力
  • 改善客户服务。

大数据的缺点:

  • 不兼容的工具
  • 安全和隐私问题
  • 文化变革的需要
  • 技术的快速变化
  • 特定的硬件需求。

2.云计算
云计算是指计算资源在互联网上的按需可用性。这些资源包括服务器、存储、数据库、软件、分析、网络和互联网上的智能,所有这些资源都可以根据客户的要求使用。在云计算中,客户必须按使用量付费。它非常灵活,可以根据需要轻松扩展资源。可以根据云供应商的要求使用所有资源,而不是物理购买任何 IT 资源。云计算具有三种服务模式,即基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS)。

提供云计算服务的云计算供应商的例子有亚马逊网络服务 (AWS)、微软 Azure、谷歌云平台、IBM 云服务等。

云计算的特点:

  • 按需可用性
  • 可通过网络访问
  • 弹性可扩展性
  • 随用随付模型
  • 多租户和资源池。

云计算的优势:

  • 备份和恢复数据
  • 改进协作
  • 出色的可达性
  • 维护成本低
  • 按需自助服务。

云计算的缺点:

  • 供应商锁定
  • 有限控制
  • 安全问题
  • 由于各种原因停机
  • 需要良好的互联网连接。

大数据与云计算的区别:

S.No. BIG DATA CLOUD COMPUTING
01. Big data refers to the data which is huge in size and also increasing rapidly with respect to time. Cloud computing refers to the on demand availability of computing resources over internet.
02. Big data includes structured data, unstructured data as well as semi-structured data. Cloud Computing Services includes Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
03. Volume of data, Velocity of data, Variety of data, Veracity of data, and Value of data are considered as the 5 most important characteristics of Big data. On-Demand availability of IT resources, broad network access, resource pooling, elasticity and measured service are considered as the main characteristics of cloud computing.
04. The purpose of big data is to organizing the large volume of data and extracting the useful information from it and using that information for the improvement of business. The purpose of cloud computing is to store and process data in cloud or availing remote IT services without physically installing any IT resources.
05. Distributed computing is used for analyzing the data and extracting the useful information. Internet is used to get the cloud based services from different cloud vendors.
06. Big data management allows centralized platform, provision for backup and recovery and low maintenance cost. Cloud computing services are cost effective, scalable and robust.
07. Some of the challenges of big data are variety of data, data storage and integration, data processing and resource management. Some of the challenges of cloud computing are availability, transformation, security concern, charging model.
08. Big data refers to huge volume of data, its management, and useful information extraction. Cloud computing refers to remote IT resources and different internet service models.
09. Big data is used to describe huge volume of data and information. Cloud computing is used to store data and information on remote servers and also processing the data using remote infrastructure.
10. Some of the sources where big data is generated includes social media data, e-commerce data, weather station data, IoT Sensor data etc. Some of the cloud computing vendors who provides cloud computing services are Amazon Web Service (AWS), Microsoft Azure, Google Cloud Platform, IBM Cloud Services etc.