Disaggregated Database Management Systems


연구 분야: Databases



학회: Technology Conference on Performance Evaluation and Benchmarking


초록

Modern applications demand high performance and cost efficient database management systems (DBMSs). Their workloads may be diverse, ranging from online transaction processing to analytics and decision support. The cloud infrastructure enables disaggregation of monolithic DBMSs into components that facilitate software-hardware co-design. This is realized using pools of hardware resources, i.e., CPUs, GPUs, memory, FPGA, NVM, etc., connected using high-speed networks. This disaggregation trend is being adopted by cloud DBMSs because hardware re-provisioning can be achieved by simply invoking software APIs. Disaggregated DBMSs separate processing from storage, enabling each to scale elastically and independently. They may disaggregate compute usage based on functionality, e.g., compute needed for writes from compute needed for queries and compute needed for compaction. They may also use disaggregated memory, e.g., for intermediate results in a shuffle or for remote caching. The DBMS monitors the characteristics of a workload and dynamically assembles its components that are most efficient and cost effective for the workload. This paper is a summary of a panel session that discussed the capability, challenges, and opportunities of these emerging DBMSs and disaggregated hardware systems.


Author Profile
Shahram Ghandeharizadeh

USC Los Angeles CA USA

Canada
Author Profile
Philip A. Bernstein

Microsoft Research Redmond WA USA

United States
Author Profile
Dhruba Borthakur

Rockset San Mateo CA USA

Canada

📄 논문 정보

발행 연도 2023년
인용수 0
출판 국가 Colombia, United States, Canada
사이트 Springer
좋아요 수 0

연관 논문 목록 (88건)