Demo Data from SIGIR 2026 / reviewers in the wild / expert
Thomas Peh
dblp:80/11411
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Indexing and storage engines › storage management
non-volatile memory integration |
0.3 | 1 | 2017 | SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017 |
Memory systems
non-volatile memory |
0.3 | 1 | 2017 | SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017 |
Indexing and storage engines
column store |
0.1 | 1 | 2012 | Efficient transaction processing in SAP HANA database: the end of a column store myth · SIGMOD Conference 2012 |
Storage systems › storage reliability
durability |
0.1 | 1 | 2017 | SAP HANA Adoption of Non-Volatile Memory · Proc. VLDB Endow. 2017 |
Database system architecture and tuning
hybrid transactional and analytical processing |
0.0 | 1 | 2012 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | SAP HANA Adoption of Non-Volatile MemoryabstractNon-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 mythabstractThe 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 Conference | 5 |