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Index
Cover
Title Page
Copyright Page
Introduction
Foolish Assumptions
Icons Used in This Book
Beyond the Book
Where to Go from Here
Part I: Getting Started with NoSQL
Chapter 1: Introducing NoSQL: The Big Picture
A Brief History of NoSQL
Features of NoSQL
Why You Should Care about NoSQL
Chapter 2: NoSQL Database Design and Terminology
Managing Different Data Types
Describing NoSQL
Applying Consistency Methods
Integrating Related Technologies
Chapter 3: Evaluating NoSQL
The Technical Evaluation
The Business Evaluation
Getting Support
Part II: Key-Value Stores
Chapter 4: Common Features of Key-Value Stores
Managing Availability
Managing Keys
Managing Data
Chapter 5: Key-Value Stores in the Enterprise
Scaling
Reducing Time to Value
Chapter 6: Key-Value Use Cases
Managing User Information
High-Speed Data Caching
Chapter 7: Key-Value Store Products
High-Speed Key Access
Taking Advantage of Flash
Using Pluggable Storage
Separating Data Storage and Distribution
Handling Partitions
Chapter 8: Riak and Basho
Choosing a Key-Value Store
Finding Riak Support (Basho)
Part III: Bigtable Clones
Chapter 9: Common Features of Bigtables
Storing Data in Bigtables
Working with Data
Managing Data
Improving Performance
Chapter 10: Bigtable in the Enterprise
Managing Multiple Data Centers
Reliability
Scalability
Chapter 11: Bigtable Use Cases
Handling Sparse Data
Analyzing Log Files
Chapter 12: Bigtable Products
Managing Tabular Big Data
Securing Your Data
High-Performing Bigtables
Distributing Data Globally
Chapter 13: Cassandra and DataStax
Designing a Modern Bigtable
Finding Support for Cassandra
Part IV: Document Databases
Chapter 14: Common Features of Document Databases
Using a Tree-Based Data Model
Document Databases as Key-Value Stores
Patching Documents
Chapter 15: Document Databases in the Enterprise
Sharding
Preventing Loss of Data
Managing Consistency
Chapter 16: Document Database Use Cases
Publishing Content
Managing Unstructured Data Feeds
Managing Changing Data Structures
Consolidating Data
Chapter 17: Document Database Products
Providing a Memcache Replacement
Providing a Familiar Developer Experience
Providing an End-to-End Document Platform
Providing a Web Application Back End
Chapter 18: MongoDB
Using an Open-Source Document Database
Finding Support for MongoDB
Part V: Graph and Triple Stores
Chapter 19: Common Features of Triple and Graph Stores
Deciding on Graph or Triple Stores
Deciding on Triples or Quads
Managing Triple Store Structures
Chapter 20: Triple Stores in the Enterprise
Ensuring Data Integrity
Storing Documents with Triples
Chapter 21: Triple Store Use Cases
Extracting Semantic Facts
Tracking Provenance
Building a Web of Facts
Managing the Social Graph
Chapter 22: Triple Store Products
Managing Documents and Triples
Scripting Graphs
Using a Distributed Graph Store
Chapter 23: Neo4j and Neo Technologies
Exploiting Neo4j
Finding Support for Neo4j
Part VI: Search Engines
Chapter 24: Common Features of Search Engines
Dissecting a Search Engine
Indexing Data Stores
Alerting
Chapter 25: Search Engines in the Enterprise
Searching the Enterprise
Creating a Search Application
Chapter 26: Search Engine Use Cases
Searching E-Commerce Products
Enterprise Data Searching
Alerting
Chapter 27: Types of Search Engines
Using Common Open-Source Text Indexing
Combining Document Stores and Search Engines
Evaluating Enterprise Search
Storing and Searching JSON
Chapter 28: Elasticsearch
Using the Elasticsearch Product
Finding Support for Elasticsearch
Part VII: Hybrid NoSQL Databases
Chapter 29: Common Hybrid NoSQL Features
The Death of Polyglot Persistence
Advantages of a Hybrid Approach
Chapter 30: Hybrid Databases in the Enterprise
Selecting a Database by Functionality
Building Mission-Critical Applications
Chapter 31: Hybrid NoSQL Database Use Cases
Digital Semantic Publishing
Metadata Catalogs
Chapter 32: Hybrid NoSQL Database Products
Managing Triples and Aggregates
Combining Documents and Triples with Enterprise Capabilities
Chapter 33: MarkLogic
Understanding MarkLogic Server
Universal Indexing
MarkLogic Corporation
Part VIII: The Part of Tens
Chapter 34: Ten Advantages of NoSQL over RDBMS
Less Need for ETL
Support for Unstructured Text
Ability to Handle Change over Time
No Reliance on SQL Magic
Ability to Scale Horizontally on Commodity Hardware
Breadth of Functionality
Support for Multiple Data Structures
Vendor Choice
No Legacy Code
Executing Code Next to the Data
Chapter 35: Ten NoSQL Misconceptions
NoSQL Is a Single Type of Database
NoSQL Databases Aren’t ACID-Compliant
NoSQL Databases Lose Data
NoSQL Databases Aren’t Ready for Mission-Critical Enterprise Applications
NoSQL Databases Aren’t Secure
All NoSQL Databases Are Open-Source
NoSQL Databases Are Only for Web 2.0 Applications
NoSQL Is Just Hype
NoSQL Developers Don’t Understand How to Use an RDBMS
Updated RDBMS Technology Will Remove the Need for NoSQL
Chapter 36: Ten Reasons Developers Love NoSQL
No Need to Write SQL
Don’t Have to Spend Months Designing Schema
Less Data Transform Code (ETL)
Easier to Maintain Code
Execute Code Close to the Data for the Best Performance
Lots of Open-Source Options
Easy to Scale
Eventual Consistency Data Model
Esoteric Language Support
JavaScript End-to-End
About the Authors
Dedication
Authors' Acknowledgments
Cheat Sheet
Connect with Dummies
End User License Agreement
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