New Product Launch: Alibaba Cloud AnalyticDB

本文涉及的产品
云原生数据仓库AnalyticDB MySQL版,基础版 8ACU 100GB 1个月
简介: If data is the new corporate currency, it is worthless without the effective use of analytics to extract that value, and yet, some 59 percent of org.

3

If data is the new corporate currency, it is worthless without the effective use of analytics to extract that value, and yet, some 59 percent of organizations believe they lack the capabilities to generate meaningful business insights from their data.

More than 80 percent of enterprise data is unstructured, which is the information that resides in emails, documents or files, for example. And yet, almost 80 percent of enterprises have little to no visibility of their unstructured data.

The other obvious challenge is simply storing and analyzing all this information, particularly as the amount of information stored in the world’s IT systems is doubling roughly every two years.

Big Data processing is a relatively new field and, as a result, very few experts are available. By 2018, the U.S. alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of Big Data to make effective decisions.

Big Data is just getting started. If you think you’ve got a lot of data to manage now, the rapid growth in adoption of the Internet of Things (IoT), machine learning and e-commerce will only bring more in the future.

This is where Big Data processing must step up to the plate to give businesses the right tools for the job. Alibaba Cloud is actively supporting organizations to overcome this challenge with a powerful product called AnalyticDB, which is a real-time Online Analytical Processing (OLAP) managed database cloud service for crunching enormous amounts of data.

Before we look at the features of AnalyticDB, it’s important to first distinguish between Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP).

In order to access and record information, databases typically store data processed in real-time, which is known as online transaction processing (OLTP). Meanwhile, OLAP, also known as an Enterprise Data Warehouse (EDW) system, stores data for the purpose of future analysis and is optimized for storing data and then performing offline analytics and creating reports.

An example of an OLTP task would be using SQL to retrieve information to process a purchase order. An e-commerce store, for instance, would need access to multiple tables in real-time to process orders, including customers’ billing information, mailing address, and the business’ inventory list. Rather than crank up a server and wait minutes to retrieve the data needed to process an order, SQL can be used to access that information and perform online transaction processing (OLTP) in real-time.

The role of OLAP is to then analyze tables of information and transactions after the purchase has taken place. This may mean analyzing transactions in relation to other transactions, i.e. what did other customers buy? Or analyzing commonalities among customer types, i.e. where they live and what time they make orders?

Ultimately, the goal of OLAP is to store data that will be analyzed later and create insight to empower decision-makers and optimize operations.

This brings us to Alibaba Cloud AnalyticDB, which integrates into your business ecosystem and equips you with the power to discover new trends through data analysis. Based on a highly available distributed system, AnalyticDB offers high-performance computing analysis of massive amounts of data, which wouldn’t be possible with a traditional OLAP engine. This includes the ability to obtain data insights sourced from multiple locations and instant processing of data in a highly concurrent and multi-dimensional analysis system.

There is no upfront costs or investment to procure equipment when using AnalyticDB as the service is hosted on the cloud and charged on a Pay-As-You-Go basis.

Below is a full comparison of AnalyticDB compared to traditional OLAP engines:

Parameter AnalyticDB Traditional OLAP Engines
Data usage Supports business-driven in-depth data exploration and interactive data analysis. Most engines primarily support data-driven computing modes for fixed report-type presentations.
Data scale The high-performance computing engine supports computing and analysis of massive data. The low-performance computing engine is able to support only a portion of the data for computation.
Engine capabilities Powered by distributed computing technology. Results can be computed quickly allowing free data exploration. Typically, no advance modeling is required. In most situations either query speeds are slow, or you must establish a cube or other models in advance and analyze the data based on this model.
Cost Under the Pay-As-You-Go model, you are only charged for the resources you actually use. Works on one-time payment or license purchase models.
Delivery Methods 1. Ready for use right after you apply. 2. Provides multi-tenant flexibility. 3. Database provisioning with a few clicks instantly.

In regards to practical application, AnalyticDB is suitable for frontend service systems which embed big data queries to gain insightful data for business processes.

For example, AnalyticDB can be used for running centralized business intelligence (BI) models, enterprises systems such as Customer Relationship Management (CRM) systems, Data Management Platforms (DMP), data report products, and other SaaS projects.

For offline computing or for stream computing, you can link the service with Alibaba Cloud MaxCompute, which is Alibaba Cloud’s platform for large-scale data warehousing. MaxCompute is different from other Big Data platforms as it is AI-enabled, guarded by Alibaba Cloud security systems and provides peak performance at a low cost. The platform offers a combination of data intelligence services, mainly for batch structural data storage and processing. It can process 100PB data in six hours, which is roughly the same amount of data as 100 million HD movies, or one-third of Facebook’s entire 300PB data warehouse.

Visit Alibaba Cloud to learn more about AnalyticDB and MaxCompute,

相关实践学习
AnalyticDB MySQL海量数据秒级分析体验
快速上手AnalyticDB MySQL,玩转SQL开发等功能!本教程介绍如何在AnalyticDB MySQL中,一键加载内置数据集,并基于自动生成的查询脚本,运行复杂查询语句,秒级生成查询结果。
阿里云云原生数据仓库AnalyticDB MySQL版 使用教程
云原生数据仓库AnalyticDB MySQL版是一种支持高并发低延时查询的新一代云原生数据仓库,高度兼容MySQL协议以及SQL:92、SQL:99、SQL:2003标准,可以对海量数据进行即时的多维分析透视和业务探索,快速构建企业云上数据仓库。 了解产品 https://www.aliyun.com/product/ApsaraDB/ads
目录
相关文章
kde
|
5天前
|
Docker镜像加速指南:手把手教你配置国内镜像源
配置国内镜像源可大幅提升 Docker 拉取速度,解决访问 Docker Hub 缓慢问题。本文详解 Linux、Docker Desktop 配置方法,并提供测速对比与常见问题解答,附最新可用镜像源列表,助力高效开发部署。
kde
3133 8
国内如何安装和使用 Claude Code镜像教程 - Windows 用户篇
国内如何安装和使用 Claude Code镜像教程 - Windows 用户篇
570 0
Dify MCP 保姆级教程来了!
大语言模型,例如 DeepSeek,如果不能联网、不能操作外部工具,只能是聊天机器人。除了聊天没什么可做的。
839 9
2025年最新版最细致Maven安装与配置指南(任何版本都可以依据本文章配置)
本文详细介绍了Maven的项目管理工具特性、安装步骤和配置方法。主要内容包括: Maven概述:解释Maven作为基于POM的构建工具,具备依赖管理、构建生命周期和仓库管理等功能。 安装步骤: 从官网下载最新版本 解压到指定目录 创建本地仓库文件夹 关键配置: 修改settings.xml文件 配置阿里云和清华大学镜像仓库以加速依赖下载 设置本地仓库路径 附加说明:包含详细的配置示例和截图指导,适用于各种操作系统环境。 本文提供了完整的Maven安装和配置
2025年最新版最细致Maven安装与配置指南(任何版本都可以依据本文章配置)
【保姆级图文详解】大模型、Spring AI编程调用大模型
【保姆级图文详解】大模型、Spring AI编程调用大模型
358 7
【保姆级图文详解】大模型、Spring AI编程调用大模型
Excel数据治理新思路:引入智能体实现自动纠错【Python+Agent】
本文介绍如何利用智能体与Python代码批量处理Excel中的脏数据,解决人工录入导致的格式混乱、逻辑错误等问题。通过构建具备数据校验、异常标记及自动修正功能的系统,将数小时的人工核查任务缩短至分钟级,大幅提升数据一致性和办公效率。
DeepSeek R1+Open WebUI实现本地知识库的搭建和局域网访问
本文介绍了使用 DeepSeek R1 和 Open WebUI 搭建本地知识库的详细步骤与注意事项,涵盖核心组件介绍、硬件与软件准备、模型部署、知识库构建及问答功能实现等内容,适用于本地文档存储、向量化与检索增强生成(RAG)场景的应用开发。
368 0
让AI时代的卓越架构触手可及,阿里云技术解决方案开放免费试用
阿里云推出基于场景的解决方案免费试用活动,新老用户均可领取100点试用点,完成部署还可再领最高100点,相当于一年可获得最高200元云资源。覆盖AI、大数据、互联网应用开发等多个领域,支持热门场景如DeepSeek部署、模型微调等,助力企业和开发者快速验证方案并上云。
306 22
让AI时代的卓越架构触手可及,阿里云技术解决方案开放免费试用
FLUX.1 Kontext 的全生态教程来啦!AIGC专区在线试玩!
Flux.1 Kontext [dev] 开源模型大家都用上了吗?小编汇总了3个使用教程,打包送上!
426 1
AI助理

你好,我是AI助理

可以解答问题、推荐解决方案等

登录插画

登录以查看您的控制台资源

管理云资源
状态一览
快捷访问