Cloud computing is a powerful technology to perform massive-scale and complex
computing. It eliminates the need to maintain expensive computing hardware, dedicated …

There is a great thrust in industry toward the development of more feasible and viable tools
for storing fast-growing volume, velocity, and diversity of data, termed 'big data'. The …

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 …

Dremel is a scalable, interactive ad-hoc query system for analysis of read-only nested data.
By combining multi-level execution trees and columnar data layout, it is capable of running …

There has been a significant amount of excitement and recent work on column-oriented
database systems (" column-stores"). These database systems have been shown to perform …

This tutorial is motivated by the clear need of many organizations, companies, and
researchers to deal with big data volumes efficiently. Examples include web analytics …

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 …

In this paper, we propose Database Processing Units, or DPUs, a class of domain-specific
database processors that can efficiently handle database applications. As a proof of …

Modern database systems for online analytical processing (OLAP) typically rely on in-
memory processing. Keeping all active data in DRAM severely limits the data capacity and …

SQL query processing for analytics over Hadoop data has recently gained significant
traction. Among many systems providing some SQL support over Hadoop, Hive is the first …