Growing main memory capacity has fueled the development of in-memory big data
management and processing. By eliminating disk I/O bottleneck, it is now possible to support …

There are two types of high-performance graph processing engines: low-and high-level
engines. Low-level engines (Galois, PowerGraph, Snap) provide optimized data structures …

In many important applications—such as search engines and relational database systems—
data are stored in the form of arrays of integers. Encoding and, most importantly, decoding of …

Requirements of enterprise applications have become much more demanding. They require
the computation of complex reports on transactional data while thousands of users may read …

In the last fifty years the world has been completely transformed through the use of IT. We
have now reached a new inflection point. This book presents, for the first time, how in …

The SAP HANA database is the core of SAP's new data management platform. The overall
goal of the SAP HANA database is to provide a generic but powerful system for different …

With the advent of cloud computing, where computational resources are expensive and data
movement needs to be secured and minimized, database management systems need to …

An exponential growth in data volume, combined with increasing demand for real-time
analysis (ie, using the most recent data), has resulted in the emergence of database systems …

The performance of the full table scan is critical for the overall performance of column-store
database systems such as the SAP HANA database. Compressing the underlying column …

Main-memory column-stores are called to efficiently use modern non-uniform memory
access (NUMA) architectures to service concurrent clients on big data. The efficient usage of …