SQL & Nosql Databases: Models, Languages, Consistency Options and Architectures for Big Data Management
暫譯: SQL 與 NoSQL 資料庫：大數據管理的模型、語言、一致性選項與架構
Meier, Andreas, Kaufmann, Michael
- 出版商: Springer Vieweg
- 出版日期: 2019-07-16
- 售價: $2,420
- 貴賓價: 9.5 折 $2,299
- 語言: 英文
- 頁數: 229
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3658245484
- ISBN-13: 9783658245481
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相關分類:
NoSQL、SQL、大數據 Big-data、資料庫
海外代購書籍(需單獨結帳)
商品描述
This book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations.
The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types:
- SQL and NoSQL databases, and their respective management systems
- The nature and uses of Big Data
- A high-level view of the organization of data management
Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more.
A full chapter probes the challenges of Ensuring Data Consistency, covering:
- Multi-User Operation
- Troubleshooting
- Consistency in Massive Distributed Data
- Comparison of the ACID and BASE consistency models, and more
System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics.
Post-Relational and NoSQL Databases
The chapter on post-relational databases discusses the limits of SQL - and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases.
A final chapter covers NoSQL Databases, along with
- Development of Non-Relational Technologies,
- Key-Value, Column-Family and Document Stores
- XML Databases and Graphic Databases, and more
SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology.
This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.
商品描述(中文翻譯)
這本書提供了關於關聯式（SQL）和非關聯式（NoSQL）資料庫的全面介紹。作者徹底回顧了當前資料庫工具和技術的狀態，並探討即將到來的創新。
本書以廣泛的資料管理概述開篇，包括資訊系統和資料庫的概述，以及當代資料庫類型的解釋：
- SQL 和 NoSQL 資料庫及其各自的管理系統
- 大數據的性質和用途
- 資料管理組織的高層次視圖
**資料建模與一致性**
本書對關聯式和圖形資料庫中的資料建模進行了章節級的探討，包括企業範圍的資料架構和資料庫設計的公式。對語言的涵蓋範圍從運算子的概述，到 SQL 和 QBE（範例查詢），再到完整性約束等。
一整章深入探討確保資料一致性的挑戰，包括：
- 多用戶操作
- 故障排除
- 大規模分散資料的一致性
- ACID 和 BASE 一致性模型的比較等
系統架構也有自己的章節，探討同質和異質資料的處理；儲存和存取結構；多維資料結構和使用 MapReduce 的平行處理等主題。
**後關聯式和 NoSQL 資料庫**
關於後關聯式資料庫的章節討論了 SQL 的限制及其以外的內容，包括多維資料庫、知識庫和模糊資料庫。
最後一章涵蓋了 NoSQL 資料庫，以及：
- 非關聯技術的發展
- 鍵值、列族和文件儲存
- XML 資料庫和圖形資料庫等
本書包含超過 100 個表格、範例和插圖，每章提供進一步閱讀的資源列表。
《SQL & NoSQL 資料庫》傳達了關聯式和非關聯式方法的優缺點，並展示了如何進行大數據應用的開發。本書對於在應用資訊技術廣泛領域工作的學生和從業者都有所裨益。
這本教科書已被德國、奧地利和瑞士的大学课程推荐和开发。
作者簡介
Andreas Meier is a former member of the Faculty of Economics and Social Science and was a professor of Information Technology at the University of Fribourg. He specializes in electronic business, electronic government, and information management. He is member of the GI (Gesellschaft für Informatik), IEEE Computer Society, and ACM. After studying music in Vienna, he graduated with a degree in mathematics at the Federal Institute of Technology (ETH) in Zurich, studied his doctorate, and qualified as a university lecture at the Institute of Computer Science. He was a systems engineer at the IBM research lab in San José, California, director of an international bank, and a member of the executive board of an insurance company.
Michael Kaufmann is a Professor of Data Science and Big Data at the School of Information Technology, Lucerne University of Applied Sciences and Arts. He is also the coordinator of the university´s Data Intelligence research team, which develops and studies methods and technologies for intelligent data management. Michael Kaufmann studied computer science, law and psychology at the University of Fribourg. With extra-occupational doctoral studies, he received his Ph.D. in computer science on the topic of inductive fuzzy classification in marketing analytics. He worked at PostFinance as a data warehouse poweruser in corporate development; Later on at Mobiliar Insurance as a data architect in the enterprise architecture unit; and as a business analyst at FIVE Informatik AG, where he initiated and led a research project and started teaching as a part time lecturer at Kalaidos University of Applied Science. Since 2014 he has been working at the Lucerne University of Applied Sciences and Arts in teaching and research as a lecturer for databases, where he founded and successfully funded the research team data intelligence.
作者簡介(中文翻譯)
安德烈亞斯·梅爾（Andreas Meier）是經濟與社會科學學院的前成員，曾任弗里堡大學資訊科技教授。他專注於電子商務、電子政府和資訊管理。他是德國資訊學會（GI）、IEEE計算機學會和ACM的成員。在維也納學習音樂後，他在蘇黎世聯邦理工學院（ETH）獲得數學學位，並在計算機科學研究所攻讀博士學位，並獲得大學講師資格。他曾在加州聖荷西的IBM研究實驗室擔任系統工程師，擔任一家國際銀行的董事，並是某保險公司的執行委員會成員。
邁克爾·考夫曼（Michael Kaufmann）是盧塞恩應用科學與藝術大學資訊科技學院的數據科學與大數據教授。他同時也是該大學數據智慧研究團隊的協調員，該團隊開發和研究智能數據管理的方法和技術。邁克爾·考夫曼在弗里堡大學學習計算機科學、法律和心理學。通過兼職的博士研究，他在市場分析中的歸納模糊分類主題上獲得計算機科學博士學位。他曾在PostFinance擔任企業發展中的數據倉庫高級用戶；後來在Mobiliar保險公司擔任企業架構單位的數據架構師；並在FIVE Informatik AG擔任商業分析師，啟動並領導了一個研究項目，並開始在Kalaidos應用科學大學擔任兼職講師。自2014年以來，他在盧塞恩應用科學與藝術大學從事教學和研究，擔任數據庫講師，並創立並成功資助了數據智慧研究團隊。
