Sofort

Oukid, Ismail; Booss, Daniel; Lehner, Wolfgang; Bumbulis, Peter; Willhalm, Thomas

doi:10.1145/2619228.2619236

Cited by 53 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…PMem is used here to store log entries and immutable snapshots. Another relatively early hybrid storage engine is SOFORT [27], designed to support both transactional and analytical workloads. It is organized column-wise.…”

Section: Pmem-aware Storage Enginesmentioning

confidence: 99%

Designing an Event Store for a Modern Three-layer Storage Hierarchy

et al. 2020

View full text Add to dashboard Cite

Event stores face the difficult challenge of continuously ingesting massive temporal data streams while satisfying demanding query and recovery requirements. Many of today’s systems deal with multiple hardware-based trade-offs. For instance, long-term storage solutions balance keeping data in cheap secondary media (SSDs, HDDs) and performance-oriented main-memory caches. As an alternative, in-memory systems focus on performance, while sacrificing monetary costs, and, to some degree, recovery guarantees. The advent of persistent memory (PMem) led to a multitude of novel research proposals aiming to alleviate those trade-offs in various fields. So far, however, there is no proposal for a PMem-powered specialized event store. Based on ChronicleDB, we will present several complementary approaches for a three-layer architecture featuring main memory, PMem, and secondary storage. We enhance some of ChronicleDB’s components with PMem for better insertion and query performance as well as better recovery guarantees. At the same time, the three-layer architecture aims to keep the overall dollar cost of a system low. The limitations and opportunities of a PMem-enhanced event store serve as important groundwork for comprehensive system design exploiting a modern storage hierarchy.

show abstract

Section: Pmem-aware Storage Enginesmentioning

confidence: 99%

Designing an Event Store for a Modern Three-layer Storage Hierarchy

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Embora NVRAM esteja atualmente disponível apenas em pequenas quantidades, especula-se que na próxima década haverão memórias PCM de 1TB e Memristors de 30TB ao preço dos discos rígidos atuais [Zhang et al 2015]. Também existem vários trabalhos explorando o uso de NVRAM para armazenamento em bancos de dados, como: [Arulraj et al 2015], [Chatzistergiou et al 2015] e [Oukid et al 2014]. Esses trabalhos utilizam simuladores de memória NVRAM para fazer seus experimentos, como o Intel Lab's NVM Hardware Emulator [Dulloor et al 2014].…”

Section: Memória Ram Não Volátilunclassified

Sistemas de Gerenciamento de Banco de Dados em Memória

Magalhães,

Monteiro,

Brayner

2018

Tópicos Em Sistemas De Informação: Minicursos SBSI 2018

View full text Add to dashboard Cite

The in-memory databases store their data directly in physical memory. This feature makes these databases provide a response time of orders of magnitude less than traditional disk-based systems. However, memory systems are more sensitive to failures, since main memory is volatile. Rather than attempting to optimize disk access, as in traditional databases, in-memory databases focus on optimizing CPU cycles and multicore processing. Differences between in-memory and disk databases affect almost every aspect of the database management, such us: data storage, indexing, concurrency control, durability and recovery techniques, and query processing and compilation. This work will discuss the main concepts and techniques that differentiate in-memory and disk resident databases. In addition, some in-memory database management systems will be introduced.

show abstract

“…Its write latency is comparable to that of DRAM, and the read latency is about 2-3 times that of DRAM. Therefore, recent studies [1,15,16,19,23,28,38,40,55,57,59,65,67,68,72] propose to store logs in NVM to improve throughput for OLTP systems. However, since TSDBMS transactions differ considerably from OLTP transactions, the use of NVM for TSDBMS logging still faces the unaddressed challenges:…”

Section: Introductionmentioning

confidence: 99%

DecLog: Decentralized Logging in Non-Volatile Memory for Time Series Database Systems

Zheng,

Gao,

Wan

et al. 2023

Proc. VLDB Endow.

View full text Add to dashboard Cite

Growing demands for the efficient processing of extreme-scale time series workloads call for more capable time series database management systems (TSDBMS). Specifically, to maintain consistency and durability of transaction processing, systems employ write-ahead logging (WAL) whereby transactions are committed only after the related log entries are flushed to disk. However, when faced with massive I/O, this becomes a throughput bottleneck. Recent advances in byte-addressable Non-Volatile Memory (NVM) provide opportunities to improve logging performance by persisting logs to NVM instead. Existing studies typically track complex transaction dependencies and use barrier instructions of NVM to ensure log ordering. In contrast, few studies consider the heavy-tailed characteristics of time series workloads, where most transactions are independent of each other. We propose DecLog, a decentralized NVM-based logging system that enables concurrent logging of TSDBMS transactions. Specifically, we propose data-driven log sequence numbering and relaxed ordering strategies to track transaction dependencies and resolve serialization issues. We also propose a parallel logging method to persist logs to NVM after being compressed and aligned. An experimental study on the YCSB-TS benchmark offers insight into the performance properties of DecLog, showing that it improves throughput by up to 4.6× while offering lower recovery time in comparison to the open source TSDBMS Beringei.

show abstract

Sofort

Cited by 53 publications

References 26 publications

Designing an Event Store for a Modern Three-layer Storage Hierarchy

Designing an Event Store for a Modern Three-layer Storage Hierarchy

Sistemas de Gerenciamento de Banco de Dados em Memória

DecLog: Decentralized Logging in Non-Volatile Memory for Time Series Database Systems

Contact Info

Product

Resources

About