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Prof. Andreas Thor

Topic:
NewSQL, SQL on Hadoop

A comparison between popular NoSQL databases and relational database management systems reveals two significant differences. Firstly, NoSQL databases typically offer a simplistic data model with limited query capabilities and lack support for powerful query languages like SQL. Secondly, they do not provide ACID transactions but instead offer limited consistency guarantees to achieve scalability and performance.

In the first part of the talk I will examine how declarative queries can be In the first part of the presentation, I will delve into the automatic translation of declarative queries for execution in a Hadoop infrastructure. As an example, I will introduce Hive, which is particularly suitable for SQL queries resembling data warehouse operations on HDFS files. Moving on to the second part, I will provide an overview of NewSQL systems, a new category of database management systems that maintain ACID guarantees. NewSQL systems such as VoltDB and Google Spanner support the relational data model and SQL while achieving scalability in distributed cloud environments.

Bio

Andreas is a full professor at the Leipzig University of Telecommunications (HfTL), a private university owned by Deutsche Telekom. Prior to joining HfTL in 2013, he served as an acting professor at the University of Passau and as a visiting research scientist at the University of Maryland. In 2008, he earned his Ph.D. in Computer Science from the University of Leipzig, where he worked as a researcher in the database group for several years.

Andreas’ research interests lie in the field of scalable data management. Specifically, he has been involved in developing approaches for entity resolution, ontology alignment, and optimizing cloud technologies. He regularly applies advanced data management techniques to research problems in the life sciences and bibliometrics.

Back to the Summer School 2016 overview

funded by:
Gefördert vom Bundesministerium für Bildung und Forschung.
Gefördert vom Freistaat Sachsen.