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Tutorial 2: Operational Analytics Data Management Systems

Presenters: Alexander Boehm (SAP), Jens Dittrich (U.of Saarland), Niloy Mukherjee (LinkedIn), Ippokratis Pandis (Amazon), Rajkumar Sen (Oracle)
Date: Mon Sep 5, 2016
Time: 9.00 a.m. - 10.30 a.m., 11:00 a.m. to 12:30 p.m.
Venue: Maple

Abstract:

As enterprise businesses become more agile and responsive to trends, sentiments and surges, business analytics applications can no longer rely on the classic data warehousing model of attempting to derive insights from data at rest. The data for analytics is as current as of the last ETL (Extract, Transform and Load) job that moved data from the operational system to the data warehouse, and business can no longer afford missing on real-time insights on the data that is fresh in the operational system. For example, a retail store could run analytics on transactional data to track sales and use the information to offer discounts. There is an increasing demand for database management systems to be able to perform real-time analytics on data that gets ingested and modified in live mainstream operational databases. As a response, many commercial vendors as well as academia have attempted to solve the problem by combining transactional and analytical processing capabilities in the same database system; these systems will be referred to as operational analytics systems.

In this tutorial, we shall present an in-depth overview of operational analytical systems. We shall start with a discussion on the various aspects associated with the design of such a system; ranging from data storage, indexing to query optimization and processing. We shall then present a set of representative systems in detail, highlight their individual architecture and design characteristics, and discuss several key research problems they address. This tutorial is intended for both researchers and practitioners in the industry.

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Bios:

Alexander Böhm is a database architect working on SAP's HANA in-memory database management system. His focus is on performance optimization and holistic improvements of enterprise architectures, in particular application server/DBMS co-design. Prior to joining SAP, he received his PhD from the University of Mannheim, Germany, where he worked on the development of efficient and scalable applications using declarative message processing.

Jens Dittrich is a full professor of Computer Science in the area of Databases, Data Management, and Big Data at Saarland University, Germany. Previous affiliations include U Marburg, SAP AG, and ETH Zurich. He received an Outrageous Ideas and Vision Paper Award at CIDR 2011, a BMBF VIP Grant in 2011, a best paper award at VLDB 2014, two CS teaching awards in 2011 and 2013, as well as several presentation awards including a qualification for the interdisciplinary German science slam finals in 2012 as well as three presentation awards at CIDR (2011, 2013, and 2015). He likes producing educational database videos (http://youtube.com/jensdit) and flipped textbooks (http://amzn.to/1Ts3rwx).

Niloy Mukherjee is a staff engineer at Distributed Data Systems, LinkedIn Corporation, working on Espresso, LinkedIn's distributed, fault-tolerant, online data store service, which currently powers major LinkedIn applications including member profiles, InMail, member engagements, desktop and mobile applications, etc. Prior to that, he has been a consulting member of technical staff at Oracle RDBMS Data and In-memory Technologies where he was one of the primary architects of Oracle Database In-memory Option, a fully consistent dual-format distributed in-memory RDBMS aimed to provide real-time analytics at scale on traditional OLAP as well as on mixed OLTAP workloads. He has published and presented his work at several VLDB, SIGMOD, and ICDE conferences, and has been awarded 20+ granted and pending patents. He has been mentioned in Business Insider as one of '26 Oracle rock star engineers changing the company'. He received his Master's degree from the Media Laboratory, Massachusetts Institute of Technology, and holds a Bachelor degree from the department of Computer Science, Indian Institute of Technology, Kharagpur.

Ippokratis Pandis is a principal engineer at Amazon Web Services working on AWS Redshift. AWS Redshift is Amazon's fully managed, petabyte scale data warehouse service. Previously, Ippokratis has held positions as software engineer at Cloudera where he worked on the Impala SQL-on-Hadoop query engine and as member of the research staff at IBM Almaden Research Center. At IBM, he was member of the team that designed and implemented the BLU column-store engine, which currently ships as part of IBM's DB2 LUW v10.5 with BLU Acceleration. Ippokratis received his PhD from Carnegie Mellon University. He is the recipient of best demonstration and paper awards at ICDE 2006, SIGMOD 2011 and CIDR 2013. He has also served as PC chair of DaMoN 2014, DaMoN 2015 and CloudDM 2016.

Rajkumar Sen is a Software Development Director at Oracle Inc. responsible for architecting Oracle's Business Intelligence Analytics for the Cloud. Prior to that, he was a Director, Engineering at MemSQL Inc. where he architected the query optimizer and the distributed query processing engine, Principal Engineer at Oracle Inc. where he developed features for the Oracle database query optimizer, and Senior Staff Engineer at Sybase Inc. where he architected the Distributed Object Lock Manager and Metadata Manager for Sybase ASE Cluster Edition. He received his Masters Degree in Computer Science with specialization in Databases from Indian Institute of Technology, Bombay in 2004 and his current research interests are in the areas of query optimization and distributed query processing.