Next Generation Databases NoSQLand Big Data

✍ Scribed by SpringerLink (Online service); Harrison, Guy

• Publisher: Apress
• Year: 2015
• Tongue: English
• Leaves: 244
• Edition: 1st ed. 2015
• Category: Library

✦ Synopsis

"It's not easy to find such a generous book on big data and databases. Fortunately, this book is the one." Feng Yu. Computing Reviews. June 28, 2016.

This is a book for enterprise architects, database administrators, and developers who need to understand the latest developments in database technologies. It is the book to help you choose the correct database technology at a time when concepts such as Big Data, NoSQL and NewSQL are making what used to be an easy choice into a complex decision with significant implications.

The relational database (RDBMS) model completely dominated database technology for over 20 years. Today this "one size fits all" stability has been disrupted by a relatively recent explosion of new database technologies. These paradigm-busting technologies are powering the "Big Data" and "NoSQL" revolutions, as well as forcing fundamental changes in databases across the board.

Deciding to use a relational database was once truly a no-brainer, and the various commercial relational databases competed on price, performance, reliability, and ease of use rather than on fundamental architectures. Today we are faced with choices between radically different database technologies. Choosing the right database today is a complex undertaking, with serious economic and technological consequences.

Next Generation Databases demystifies today's new database technologies. The book describes what each technology was designed to solve. It shows how each technology can be used to solve real word application and business problems. Most importantly, this book highlights the architectural differences between technologies that are the critical factors to consider when choosing a database platform for new and upcoming projects.


Introduces the new technologies that have revolutionized the database landscape


Describes how each technology can be used to solve specific application or business challenges


Reviews the most popular new wave databases and how they use these new database technologies

✦ Table of Contents

Contents at a Glance......Page 5
Contents......Page 6
About the Author......Page 15
About the Technical Reviewer......Page 16
Acknowledgements......Page 17
Part I: Next Generation Databases......Page 18
Chapter 1: Three Database Revolutions......Page 19
Early Database Systems......Page 20
The First Database Revolution......Page 22
The Second Database Revolution......Page 23
Relational theory......Page 24
Transaction Models......Page 25
Database Wars!......Page 26
Object-oriented Programming and the OODBMS......Page 27
The Third Database Revolution......Page 29
The Rest of the Web......Page 30
Document Databases......Page 31
The Nonrelational Explosion......Page 32
Conclusion: One Size Doesn’t Fit All......Page 33
Notes......Page 34
The Big Data Revolution......Page 36
Cloud, Mobile, Social, and Big Data......Page 37
Google Hardware......Page 38
The Google Software Stack......Page 40
More about MapReduce......Page 41
Hadoop: Open-Source Google Stack......Page 42
The Power of Hadoop......Page 43
Hadoop’s Architecture......Page 44
HBase......Page 47
Hive......Page 49
Pig......Page 51
Notes......Page 52
Scaling Web 2.0......Page 53
The Open-source Solution......Page 54
Sharding......Page 55
CAP Theorem......Page 57
Eventual Consistency......Page 58
Amazon’s Dynamo......Page 59
Consistent Hashing......Page 61
Tunable Consistency......Page 63
Note......Page 65
Chapter 4: Document Databases......Page 66
XML Tools and Standards......Page 67
XML Databases......Page 68
JSON and AJAX......Page 70
JSON Databases......Page 71
Data Models in Document Databases......Page 73
MongoDB......Page 74
Conclusion......Page 76
What is a Graph?......Page 77
RDBMS Patterns for Graphs......Page 79
RDF and SPARQL......Page 80
Property Graphs and Neo4j......Page 81
Gremlin......Page 83
Graph Compute Engines......Page 85
Conclusion......Page 86
Data Warehousing Schemas......Page 87
The Columnar Alternative......Page 89
Columnar Write Penalty......Page 91
Column Database Architectures......Page 93
Projections......Page 94
Columnar Technology in Other Databases......Page 96
Note......Page 97
The End of Disk?......Page 98
Solid State Disk......Page 99
The Economics of Disk......Page 100
SSD- Enabled Databases......Page 101
In-Memory Databases......Page 102
TimesTen......Page 103
Redis......Page 104
SAP HANA......Page 106
VoltDB......Page 108
Oracle 12c “in-Memory Database”......Page 109
Berkeley Analytics Data Stack and Spark......Page 110
Spark Architecture......Page 112
Note......Page 113
Part II: The Gory Details......Page 114
Distributed Relational Databases......Page 115
Shared Nothing and Shared Disk......Page 117
Sharding......Page 120
Sharding Mechanisms......Page 121
Replication......Page 123
HBase......Page 125
Tables, Regions, and RegionServers......Page 126
Caching and Data Locality......Page 127
Rowkey Ordering......Page 128
Gossip......Page 129
Consistent Hashing......Page 130
Replicas......Page 134
Summary......Page 136
Types of Consistency......Page 137
ACID and MVCC......Page 138
Other Levels of Consistency......Page 140
MongoDB Locking......Page 141
Eventually Consistent Region Replicas......Page 142
Write Consistency......Page 144
Interaction between Consistency Levels......Page 145
Hinted Handoff and Read Repair......Page 146
Timestamps and Granularity......Page 147
Vector Clocks......Page 148
Lightweight Transactions......Page 150
Conclusion......Page 153
Data Models......Page 155
Review of the Relational Model of Data......Page 156
Convergent Replicated Data Types......Page 158
Column Family Structure......Page 161
Versions......Page 162
Cassandra......Page 163
Cassandra Collections......Page 165
JSON Data Models......Page 166
Storage......Page 167
Typical Relational Storage Model......Page 168
Log-structured Merge Trees......Page 170
SSTables and Bloom Filters......Page 171
Compaction......Page 172
DIY Secondary Indexing......Page 173
Global and Local Indexes......Page 175
Conclusion......Page 176
SQL......Page 177
Riak......Page 179
Hbase......Page 181
MongoDB......Page 183
Cassandra Query Language ( CQL)......Page 185
MapReduce......Page 187
Pig......Page 189
Spark......Page 191
The Return of SQL......Page 192
Hive......Page 193
Impala......Page 194
Couchbase N1QL......Page 195
Apache Drill......Page 198
Note......Page 200
The Revolution Revisited......Page 201
Counterrevolutionaries......Page 202
Have We Come Full Circle?......Page 203
An Embarrassment of Choice......Page 204
Consistency Models......Page 205
Schema......Page 206
Database Languages......Page 208
Storage......Page 209
A Vision for a Converged Database......Page 210
Meanwhile, Back at Oracle HQ .........Page 211
Oracle JSON Support......Page 212
Accessing JSON via Oracle REST......Page 214
REST Access to Oracle Tables......Page 216
Oracle Graph......Page 217
Oracle Sharding......Page 218
Other Convergent Databases......Page 220
Storage Technologies......Page 221
Blockchain......Page 222
Quantum Computing......Page 223
Conclusion......Page 224
Notes......Page 225
Aerospike......Page 226
Cassandra......Page 227
DynamoDB......Page 228
HBase......Page 229
MongoDB......Page 230
Neo4J......Page 231
Oracle RDBMS......Page 232
Redis......Page 233
SAP HANA......Page 234
TimesTen......Page 235
VoltDB......Page 236
Index......Page 238