NoSQL For Dummies

NoSQL For Dummies

by Adam Fowler
Released February 2015
Publisher(s): For Dummies
ISBN: 9781118905746

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Book description

Get up to speed on the nuances of NoSQL databases and what they mean for your organization

This easy to read guide to NoSQL databases provides the type of no-nonsense overview and analysis that you need to learn, including what NoSQL is and which database is right for you. Featuring specific evaluation criteria for NoSQL databases, along with a look into the pros and cons of the most popular options, NoSQL For Dummies provides the fastest and easiest way to dive into the details of this incredible technology. You'll gain an understanding of how to use NoSQL databases for mission-critical enterprise architectures and projects, and real-world examples reinforce the primary points to create an action-oriented resource for IT pros.

If you're planning a big data project or platform, you probably already know you need to select a NoSQL database to complete your architecture. But with options flooding the market and updates and add-ons coming at a rapid pace, determining what you require now, and in the future, can be a tall task. This is where NoSQL For Dummies comes in!

  • Learn the basic tenets of NoSQL databases and why they have come to the forefront as data has outpaced the capabilities of relational databases
  • Discover major players among NoSQL databases, including Cassandra, MongoDB, MarkLogic, Neo4J, and others
  • Get an in-depth look at the benefits and disadvantages of the wide variety of NoSQL database options
  • Explore the needs of your organization as they relate to the capabilities of specific NoSQL databases

Big data and Hadoop get all the attention, but when it comes down to it, NoSQL databases are the engines that power many big data analytics initiatives. With NoSQL For Dummies, you'll go beyond relational databases to ramp up your enterprise's data architecture in no time.

Table of contents

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

Product information

  • Title: NoSQL For Dummies
  • Author(s): Adam Fowler
  • Release date: February 2015
  • Publisher(s): For Dummies
  • ISBN: 9781118905746