[{"createTime":1735734952000,"id":1,"img":"hwy_ms_500_252.jpeg","link":"https://activity.huaweicloud.com/cps.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=V1g3MDY4NTY=&utm_medium=cps&utm_campaign=201905","name":"华为云秒杀","status":9,"txt":"华为云38元秒杀","type":1,"updateTime":1735747411000,"userId":3},{"createTime":1736173885000,"id":2,"img":"txy_480_300.png","link":"https://cloud.tencent.com/act/cps/redirect?redirect=1077&cps_key=edb15096bfff75effaaa8c8bb66138bd&from=console","name":"腾讯云秒杀","status":9,"txt":"腾讯云限量秒杀","type":1,"updateTime":1736173885000,"userId":3},{"createTime":1736177492000,"id":3,"img":"aly_251_140.png","link":"https://www.aliyun.com/minisite/goods?userCode=pwp8kmv3","memo":"","name":"阿里云","status":9,"txt":"阿里云2折起","type":1,"updateTime":1736177492000,"userId":3},{"createTime":1735660800000,"id":4,"img":"vultr_560_300.png","link":"https://www.vultr.com/?ref=9603742-8H","name":"Vultr","status":9,"txt":"Vultr送$100","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":5,"img":"jdy_663_320.jpg","link":"https://3.cn/2ay1-e5t","name":"京东云","status":9,"txt":"京东云特惠专区","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":6,"img":"new_ads.png","link":"https://www.iodraw.com/ads","name":"发布广告","status":9,"txt":"发布广告","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":7,"img":"yun_910_50.png","link":"https://activity.huaweicloud.com/discount_area_v5/index.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=aXhpYW95YW5nOA===&utm_medium=cps&utm_campaign=201905","name":"底部","status":9,"txt":"高性能云服务器2折起","type":2,"updateTime":1735660800000,"userId":3}]
一、 数据库概述
存储和管理数据作为计算机应用的重要基础,其发展经历了三个阶段:手工管理、文件管理和数据库管理。使用数据库来管理数据,使得大型计算机的广泛应用成为可能。数据库技术历经半个多世纪的发展,已经取得了很大的进步。
云计算在快速发展的同时也催生了各种类型网络应用的兴起,这些应用同时也对数据库系统相关的架构、存储策略、数据模型、访问接口等关键技术提出了新的需求,我们先来看看随着软件行业的发展,关系型数据库面临了哪些挑战。
1)高并发
一个最典型的就是电商网站,例如双11,几亿大军的点击造成在某一时刻的并发量是很高的,传统的关系型数据库肯定已经是不堪重负了,如Oracle的Session数量推荐的才只有500。随着系统投入运营,数据量以飞快的速度增长,面对用户频繁读写请求带来的巨大并发量,关系数据库常由于复杂的逻辑设计导致响应慢甚至死锁等问题,
降低了并发读写的性能。
2)高效率存储海量数据
大数据时代,数据量已经不是用GB、TB来衡量了,而是EB、ZB了,面对这海量的数据,如何高效率的存储这些数据,关系型数据库无法解决这个问题,以Oracle为例,单机的物理扩展不仅成本高,而且难度也加大了。
像Facebook、Twitter、新浪微博等 Web2.0
社交类网站,用户既是网站内容的浏览者,同时也是网站内容的创造者,数亿用户的频繁使用会使网站在短期内积聚巨大的数据量,面对如此庞大用户群产生的海量用户动态,试想关系数据库在有着数亿条记录