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| Preface | |
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| Understand | |
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| Why NoSQL? | |
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| The Value of Relational Databases | |
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| Getting at Persistent Data | |
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| Concurrency | |
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| Integration | |
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| A (Mostly) Standard Model | |
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| Impedance Mismatch | |
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| Application and Integration Databases | |
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| Attack of the Clusters | |
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| The Emergence of NoSQL | |
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| Key Points | |
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| Aggregate Data Models | |
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| Aggregates | |
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| Example of Relations and Aggregates | |
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| Consequences of Aggregate Orientation | |
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| Key-Value and Document Data Models | |
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| Column-Family Stores | |
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| Summarizing Aggregate-Oriented Databases | |
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| Further Reading | |
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| Key Points | |
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| More Details on Data Models | |
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| Relationships | |
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| Graph Databases | |
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| Schemaless Databases | |
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| Materialized Views | |
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| Modeling for Data Access | |
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| Key Points | |
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| Distribution Models | |
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| Single Server | |
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| Sharding | |
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| Master-Slave Replication | |
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| Peer-to-Peer Replication | |
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| Combining Sharding and Replication | |
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| Key Points | |
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| Consistency | |
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| Update Consistency | |
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| Read Consistency | |
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| Relaxing Consistency | |
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| The CAP Theorem | |
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| Relaxing Durability | |
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| Quorums | |
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| Further Reading | |
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| Key Points | |
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| Version Stamps | |
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| Business and System Transactions | |
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| Version Stamps on Multiple Nodes | |
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| Key Points | |
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| Map-Reduce | |
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| Basic Map-Reduce | |
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| Partitioning and Combining | |
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| Composing Map-Reduce Calculations | |
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| A Two Stage Map-Reduce Example | |
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| Incremental Map-Reduce | |
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| Further Reading | |
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| Key Points | |
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| Implement | |
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| Key-Value Databases | |
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| What Is a Key-Value Store | |
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| Key-Value Store Features | |
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| Consistency | |
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| Transactions | |
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| Query Features | |
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| Structure of Data | |
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| Scaling | |
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| Suitable Use Cases | |
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| Storing Session Information | |
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| User Profiles, Preferences | |
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| Shopping Cart Data | |
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| When Not to Use | |
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| Relationships among Data | |
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| Multioperation Transactions | |
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| Query by Data | |
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| Operations by Sets | |
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| Document Databases | |
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| What Is a Document Database? | |
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| Features | |
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| Consistency | |
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| Transactions | |
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| Availability | |
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| Query Features | |
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| Scaling | |
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| Suitable Use Cases | |
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| Event Logging | |
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| Content Management Systems, Blogging Platforms | |
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| Web Analytics or Real-Time Analytics | |
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| E-Commerce Applications | |
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| When Not to Use | |
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| Complex Transactions Spanning Different Operations | |
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| Queries against Varying Aggregate Structure | |
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| Column-Family Stores | |
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| What Is a Column-Family Data Store? | |
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| Features | |
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| Consistency | |
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| Transactions | |
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| Availability | |
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| Query Features | |
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| Scaling | |
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| Suitable Use Cases | |
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| Event Logging | |
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| Content Management Systems, Blogging Platforms | |
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| Counters | |
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| Expiring Usage | |
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| When Not to Use | |
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| Graph Databases | |
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| What Is a Graph Database? | |
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| Features | |
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| Consistency | |
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| Transactions | |
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| Availability | |
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| Query Features | |
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| Scaling | |
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| Suitable Use Cases | |
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| Connected Data | |
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| Routing, Dispatch, and Location-Based Services | |
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| Recommendation Engines | |
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| When Not to Use | |
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| Schema Migrations | |
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| Schema Changes | |
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| Schema Changes in RDBMS | |
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| Migrations for Green Field Projects | |
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| Migrations in Legacy Projects | |
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| Schema Changes in a NoSQL Data Store | |
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| Incremental Migration | |
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| Migrations in Graph Databases | |
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| Changing Aggregate Structure | |
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| Further Reading | |
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| Key Points | |
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| Polyglot Persistence | |
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| Disparate Data Storage Needs | |
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| Polyglot Data Store Usage | |
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| Service Usage over Direct Data Store Usage | |
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| Expanding for Better Functionality | |
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| Choosing the Right Technology | |
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| Enterprise Concerns with Polyglot Persistence | |
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| Deployment Complexity | |
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| Key Points | |
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| Beyond NoSQL | |
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| File Systems | |
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| Event Sourcing | |
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| Memory Image | |
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| Version Control | |
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| XML Databases | |
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| Object Databases | |
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| Key Points | |
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| Choosing Your Database | |
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| Programmer Productivity | |
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| Data-Access Performance | |
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| Sticking with the Default | |
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| Hedging Your Bets | |
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| Key Points | |
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| Final Thoughts | |
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| Bibliography | |
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| Index | |