You are previewing Professional NoSQL.

Professional NoSQL

Cover of Professional NoSQL by Shashank Tiwari Published by Wrox
  1. Cover
  2. Contents
  3. Introduction
  4. Part I: Getting Started
    1. Chapter 1: NoSQL: What It Is and Why You Need it
      1. Definition and Introduction
      2. Sorted Ordered Column-Oriented Stores
      3. Key/Value Stores
      4. Document Databases
      5. Graph Databases
      6. Summary
    2. Chapter 2: Hello NoSQL: Getting Initial Hands-on Experience
      1. First Impressions — Examining Two Simple Examples
      2. Working with Language Bindings
      3. Summary
    3. Chapter 3: Interfacing and Interacting with NoSQL
      1. If No SQL, Then What?
      2. Language Bindings for NoSQL Data Stores
      3. Summary
  5. Part II: Learning the NoSQL Basics
    1. Chapter 4: Understanding the Storage Architecture
      1. Working with Column-Oriented Databases
      2. HBase Distributed Storage Architecture
      3. Document Store Internals
      4. Understanding Key/Value Stores in Memcached and Redis
      5. Eventually Consistent Non-relational Databases
      6. Summary
    2. Chapter 5: Performing CRUD Operations
      1. Creating Records
      2. Accessing Data
      3. Updating and Deleting Data
      4. Summary
    3. Chapter 6: Querying NoSQL Stores
      1. Similarities Between SQL and MongoDB Query Features
      2. Accessing Data from Column-Oriented Databases Like HBase
      3. Querying Redis Data Stores
      4. Summary
    4. Chapter 7: Modifying Data Stores and Managing Evolution
      1. Changing Document Databases
      2. Schema Evolution in Column-Oriented Databases
      3. HBase Data Import and Export
      4. Data Evolution in Key/Value Stores
      5. Summary
    5. Chapter 8: Indexing and Ordering Data Sets
      1. Essential Concepts Behind a Database Index
      2. Indexing and Ordering in MongoDB
      3. Creating and Using Indexes in MongoDB
      4. Indexing and Ordering in CouchDB
      5. Indexing in Apache Cassandra
      6. Summary
    6. Chapter 9: Managing Transactions and Data Integrity
      1. RDBMS AND ACID
      2. Distributed ACID Systems
      3. Upholding CAP
      4. Consistency Implementations in a Few NoSQL Products
      5. Summary
  6. Part III: Gaining Proficiency with NoSQL
    1. Chapter 10: Using NoSQL in the Cloud
      1. Google App Engine Data Store
      2. Amazon SimpleDB
      3. Summary
    2. Chapter 11: Scalable Parallel Processing with MapReduce
      1. Understanding MapReduce
      2. MapReduce with HBase
      3. MapReduce Possibilities and Apache Mahout
      4. Summary
    3. Chapter 12: Analyzing Big Data with Hive
      1. Hive Basics
      2. Back to Movie Ratings
      3. Good Old SQL
      4. JOIN(s) in Hive QL
      5. Summary
    4. Chapter 13: Surveying Database Internals
      1. MongoDB Internals
      2. Membase Architecture
      3. Hypertable Under the Hood
      4. Apache Cassandra
      5. Berkeley DB
      6. Summary
  7. Part IV: Mastering NoSQL
    1. Chapter 14: Choosing Among NoSQL Flavors
      1. Comparing NoSQL Products
      2. Benchmarking Performance
      3. Contextual Comparison
      4. Summary
    2. Chapter 15: Coexistence
      1. Using MySQL as a NoSQL Solution
      2. Mostly Immutable Data Stores
      3. Web Frameworks and NoSQL
      4. Migrating from RDBMS to NoSQL
      5. Summary
    3. Chapter 16: Performance Tuning
      1. Goals of Parallel Algorithms
      2. Influencing Equations
      3. Partitioning
      4. Scheduling in Heterogeneous Environments
      5. Additional MapReduce Tuning
      6. HBase Coprocessors
      7. Leveraging Bloom Filters
      8. Summary
    4. Chapter 17: Tools and Utilities
      1. RRDTool
      2. Nagios
      3. Scribe
      4. Flume
      5. Chukwa
      6. Pig
      7. Nodetool
      8. OpenTSDB
      9. Solandra
      10. Hummingbird and C5t
      11. GeoCouch
      12. Alchemy Database
      13. Webdis
      14. Summary
  8. Appendix: Installation and Setup Instructions
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Chapter 9

Managing Transactions and Data Integrity

WHAT’S IN THIS CHAPTER?

  • Understanding essentials of ACID transactions
  • Applying transactional guarantee in distributed systems
  • Understanding Brewer’s CAP Theorem
  • Exploring transactional support in NoSQL products

The best way to understand transactions and data integrity in the world of NoSQL is to first review these same concepts in the context of the familiar RDBMS environment. Once the fundamental transactional notions and vocabulary are established and a couple of use cases are illustrated, it gets easier to conceive how the transactional concepts are challenged in large-scale distributed environments; places where NoSQL shines.

Not all NoSQL products share a similar view of transactions and data integrity. So once the broad and generalized expectations of transactional integrity in large-scale distributed systems is explained, it’s pertinent to show how it’s implemented in specific products and that is exactly how this chapter approaches the topic.

So to get started, you need to begin with ACID.

RDBMS AND ACID

ACID, which stands for Atomicity, Consistency, Isolation, and Durability, has become the gold standard to define the highest level of transactional integrity in database systems. As the acronym suggests it implies the following:

  • Atomicity — Either a transactional operation fully succeeds or completely fails. Nothing that is inconsistent between the two states is acceptable. The canonical example that illustrates this ...

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