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E-raamat: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence

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  • Formaat: 192 pages
  • Ilmumisaeg: 01-Aug-2012
  • Kirjastus: Addison-Wesley Educational Publishers Inc
  • Keel: eng
  • ISBN-13: 9780133018004
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NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot PersistenceSuurem pilt
  • Formaat: 192 pages
  • Ilmumisaeg: 01-Aug-2012
  • Kirjastus: Addison-Wesley Educational Publishers Inc
  • Keel: eng
  • ISBN-13: 9780133018004
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The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational NoSQL databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program.

 

NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further.

 

The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j.

 

In addition, by drawing on Pramod Sadalages pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access.

 
Preface xiii
Part I Understand
1(78)
Chapter 1 Why NoSQL?
3(10)
1.1 The Value of Relational Databases
3(2)
1.1.1 Getting at Persistent Data
3(1)
1.1.2 Concurrency
4(1)
1.1.3 Integration
4(1)
1.1.4 A (Mostly) Standard Model
4(1)
1.2 Impedance Mismatch
5(1)
1.3 Application and Integration Databases
6(2)
1.4 Attack of the Clusters
8(1)
1.5 The Emergence of NoSQL
9(3)
1.6 Key Points
12(1)
Chapter 2 Aggregate Data Models
13(12)
2.1 Aggregates
14(6)
2.1.1 Example of Relations and Aggregates
14(5)
2.1.2 Consequences of Aggregate Orientation
19(1)
2.2 Key-Value and Document Data Models
20(1)
2.3 Column-Family Stores
21(2)
2.4 Summarizing Aggregate-Oriented Databases
23(1)
2.5 Further Reading
24(1)
2.6 Key Points
24(1)
Chapter 3 More Details on Data Models
25(12)
3.1 Relationships
25(1)
3.2 Graph Databases
26(2)
3.3 Schemaless Databases
28(2)
3.4 Materialized Views
30(1)
3.5 Modeling for Data Access
31(5)
3.6 Key Points
36(1)
Chapter 4 Distribution Models
37(10)
4.1 Single Server
37(1)
4.2 Sharding
38(2)
4.3 Master-Slave Replication
40(2)
4.4 Peer-to-Peer Replication
42(1)
4.5 Combining Sharding and Replication
43(1)
4.6 Key Points
44(3)
Chapter 5 Consistency
47(14)
5.1 Update Consistency
47(2)
5.2 Read Consistency
49(3)
5.3 Relaxing Consistency
52(4)
5.3.1 The CAP Theorem
53(3)
5.4 Relaxing Durability
56(1)
5.5 Quorums
57(2)
5.6 Further Reading
59(1)
5.7 Key Points
59(2)
Chapter 6 Version Stamps
61(6)
6.1 Business and System Transactions
61(2)
6.2 Version Stamps on Multiple Nodes
63(2)
6.3 Key Points
65(2)
Chapter 7 Map-Reduce
67(12)
7.1 Basic Map-Reduce
68(1)
7.2 Partitioning and Combining
69(3)
7.3 Composing Map-Reduce Calculations
72(5)
7.3.1 A Two Stage Map-Reduce Example
73(3)
7.3.2 Incremental Map-Reduce
76(1)
7.4 Further Reading
77(1)
7.5 Key Points
77(2)
Part II Implement
79(74)
Chapter 8 Key-Value Databases
81(8)
8.1 What Is a Key-Value Store
81(2)
8.2 Key-Value Store Features
83(4)
8.2.1 Consistency
83(1)
8.2.2 Transactions
84(1)
8.2.3 Query Features
84(2)
8.2.4 Structure of Data
86(1)
8.2.5 Scaling
86(1)
8.3 Suitable Use Cases
87(1)
8.3.1 Storing Session Information
87(1)
8.3.2 User Profiles, Preferences
87(1)
8.3.3 Shopping Cart Data
87(1)
8.4 When Not to Use
87(2)
8.4.1 Relationships among Data
87(1)
8.4.2 Multioperation Transactions
88(1)
8.4.3 Query by Data
88(1)
8.4.4 Operations by Sets
88(1)
Chapter 9 Document Databases
89(10)
9.1 What Is a Document Database?
90(1)
9.2 Features
91(6)
9.2.1 Consistency
91(1)
9.2.2 Transactions
92(1)
9.2.3 Availability
93(1)
9.2.4 Query Features
94(1)
9.2.5 Scaling
95(2)
9.3 Suitable Use Cases
97(1)
9.3.1 Event Logging
97(1)
9.3.2 Content Management Systems, Blogging Platforms
98(1)
9.3.3 Web Analytics or Real-Time Analytics
98(1)
9.3.4 E-Commerce Applications
98(1)
9.4 When Not to Use
98(1)
9.4.1 Complex Transactions Spanning Different Operations
98(1)
9.4.2 Queries against Varying Aggregate Structure
98(1)
Chapter 10 Column-Family Stores
99(12)
10.1 What Is a Column-Family Data Store?
99(1)
10.2 Features
100(5)
10.2.1 Consistency
103(1)
10.2.2 Transactions
104(1)
10.2.3 Availability
104(1)
10.2 A Query Features
105(2)
10.2.5 Scaling
107(1)
10.3 Suitable Use Cases
107(2)
10.3.1 Event Logging
107(1)
10.3.2 Content Management Systems, Blogging Platforms
108(1)
10.3.3 Counters
108(1)
10.3.4 Expiring Usage
108(1)
10.4 When Not to Use
109(2)
Chapter 11 Graph Databases
111(12)
11.1 What Is a Graph Database?
111(2)
11.2 Features
113(7)
11.2.1 Consistency
114(1)
11.2.2 Transactions
114(1)
11.2.3 Availability
115(1)
11.2.4 Query Features
115(4)
11.2.5 Scaling
119(1)
11.3 Suitable Use Cases
120(1)
11.3.1 Connected Data
120(1)
11.3.2 Routing, Dispatch, and Location-Based Services
120(1)
11.3.3 Recommendation Engines
121(1)
11.4 When Not to Use
121(2)
Chapter 12 Schema Migrations
123(10)
12.1 Schema Changes
123(1)
12.2 Schema Changes in RDBMS
123(5)
12.2.1 Migrations for Green Field Projects
124(2)
12.2.2 Migrations in Legacy Projects
126(2)
12.3 Schema Changes in a NoSQL Data Store
128(4)
12.3.1 Incremental Migration
130(1)
12.3.2 Migrations in Graph Databases
131(1)
12.3.3 Changing Aggregate Structure
132(1)
12.4 Further Reading
132(1)
12.5 Key Points
132(1)
Chapter 13 Polyglot Persistence
133(8)
13.1 Disparate Data Storage Needs
133(1)
13.2 Polyglot Data Store Usage
134(2)
13.3 Service Usage over Direct Data Store Usage
136(1)
13.4 Expanding for Better Functionality
136(2)
13.5 Choosing the Right Technology
138(1)
13.6 Enterprise Concerns with Polyglot Persistence
138(1)
13.7 Deployment Complexity
139(1)
13.8 Key Points
140(1)
Chapter 14 Beyond NoSQL
141(6)
14.1 File Systems
141(1)
14.2 Event Sourcing
142(2)
14.3 Memory Image
144(1)
14.4 Version Control
145(1)
14.5 XML Databases
145(1)
14.6 Object Databases
146(1)
14.7 Key Points
146(1)
Chapter 15 Choosing Your Database
147(6)
15.1 Programmer Productivity
147(2)
15.2 Data-Access Performance
149(1)
15.3 Sticking with the Default
150(1)
15.4 Hedging Your Bets
150(1)
15.5 Key Points
151(1)
15.6 Final Thoughts
152(1)
Bibliography 153(4)
Index 157
Pramod J. Sadalage, Principal Consultant at ThoughtWorks, enjoys the rare role of bridging the divide between database professionals and application developers. He regularly consults with clients who have particularly challenging data needs requiring new technologies and techniques. He developed pioneering techniques that allowed relational databases to be designed in an evolutionary manner based on version-controlled schema migrations. With Scott Ambler, he coauthored Refactoring Databases(Addison-Wesley, 2006).

 

Martin Fowler, Chief Scientist at ThoughtWorks, focuses on better ways to design software systems and improve developer productivity. His books include Patterns of Enterprise Application Architecture; UML Distilled, Third Edition; Domain-Specific Languages (with Rebecca Parsons); and Refactoring: Improving the Design of Existing Code (with Kent Beck, John Brant, and William Opdyke). All are published by Addison-Wesley.
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