A Course in In-Memory Data Management

A Course in In-Memory Data Management: The Inner Mechanics of In-Memory Databases

Recent achievements in hardware and software development, such as multi-core CPUs and DRAM capacities of multiple terabytes per server, enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of enterprise data. Professor Hasso Plattner and his research group at the Hasso Plattner Institute in Potsdam, Germany, have been investigating and teaching the corresponding concepts and their adoption in the software industry for years.

This book is based on the first online course on the openHPI e-learning platform, which was launched in autumn 2012 with more than 13,000 learners. The book is designed for students of computer science, software engineering, and IT related subjects. However, it addresses business experts, decision makers, software developers, technology experts, and IT analysts alike. Plattner and his group focus on exploring the inner mechanics of a column-oriented dictionary-encoded in-memory database. Covered topics include – amongst others – physical data storage and access, basic database operators, compression mechanisms, and parallel join algorithms. Beyond that, implications for future enterprise applications and their development are discussed. Readers are lead to understand the radical differences and advantages of the new technology over traditional row-oriented disk-based databases.

Table of Contents

1 Introduction

Part I The Future of Enterprise Computing
2 New Requirements for Enterprise Computing
3 Enterprise Application Characteristics
4 Changes in Hardware
5 A Blueprint of SanssouciDB

Part II Foundations of Database Storage Techniques
6 Dictionary Encoding
7 Compression
8 Data Layout in Main Memory
9 Partitioning

Part III In-Memory Database Operators
10 Delete
11 Insert
12 Update
13 Tuple Reconstruction
14 Scan Performance
15 Select
16 Materialization Strategies
17 Parallel Data Processing
18 Indices
19 Join
20 Aggregate Functions
21 Parallel Select
22 Workload Management and Scheduling
23 Parallel Join
24 Parallel Aggregation

Part IV Advanced Database Storage Techniques
25 Differential Buffer
26 Insert-Only
27 The Merge Process
28 Logging
29 Recovery
30 On-the-Fly Database Reorganization

Part V Foundations for a New Enterprise Application Development Era
31 Implications on Application Development
32 Database Views
33 Handling Business Objects
34 Bypass Solution