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Thomas Peh

dblp:80/11411 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Indexing and storage engines · 70% Transaction processing and concurrency control · 23% Database system architecture and tuning · 7%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 77% Storage systems · 23%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Indexing and storage engines › storage management
non-volatile memory integration
0.312017
SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017
Memory systems
non-volatile memory
0.312017
SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017
Indexing and storage engines
column store
0.112012
Efficient transaction processing in SAP HANA database: the end of a column store myth · SIGMOD Conference 2012
Storage systems › storage reliability
durability
0.112017
SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017
Database system architecture and tuning
hybrid transactional and analytical processing
0.012012
Efficient transaction processing in SAP HANA database: the end of a column store myth · SIGMOD Conference 2012

Methods — techniques the papers use, named apart from their topics

byte-addressable NVRAM · 0.6
YearPublicationVenuePosition
2017 SAP HANA Adoption of Non-Volatile Memory
abstract
Non-Volatile RAM (NVRAM) is a novel class of hardware technology which is an interesting blend of two storage paradigms: byte-addressable DRAM and block-addressable storage (e.g. HDD/SSD). Most of the existing enterprise relational data management systems such as SAP HANA have their internal architecture based on the inherent assumption that memory is volatile and base their persistence on explicit handling of block-oriented storage devices. In this paper, we present the early adoption of Non-Volatile Memory within the SAP HANA Database, from the architectural and technical angles. We discuss our architectural choices, dive deeper into a few challenges of the NVRAM integration and their solutions, and share our experimental results. As we present our solutions for the NVRAM integration, we also give, as a basis, a detailed description of the relevant HANA internals.
Mihnea Andrei, Christian Lemke, Günter Radestock, Robert Schulze, Carsten Thiel, Rolando Blanco, Akanksha Meghlan, Muhammad Sharique, Sebastian Seifert, Surendra Vishnoi, Daniel Booss, Thomas Peh, Ivan Schreter, Werner Thesing, Mehul Wagle, Thomas Willhalm
Proc. VLDB Endow.12
2012 Efficient transaction processing in SAP HANA database: the end of a column store myth
abstract
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 query scenarios, both transactional and analytical, on the same data representation within a highly scalable execution environment. Within this paper, we highlight the main features that differentiate the SAP HANA database from classical relational database engines. Therefore, we outline the general architecture and design criteria of the SAP HANA in a first step. In a second step, we challenge the common belief that column store data structures are only superior in analytical workloads and not well suited for transactional workloads. We outline the concept of record life cycle management to use different storage formats for the different stages of a record. We not only discuss the general concept but also dive into some of the details of how to efficiently propagate records through their life cycle and moving database entries from write-optimized to read-optimized storage formats. In summary, the paper aims at illustrating how the SAP HANA database is able to efficiently work in analytical as well as transactional workload environments.
Vishal Sikka, Franz Färber, Wolfgang Lehner, Sang Kyun Cha, Thomas Peh, Christof Bornhövd
SIGMOD Conference5