DBOS

Author:

Skiadopoulos Athinagoras1,Li Qian1,Kraft Peter1,Kaffes Kostis1,Hong Daniel2,Mathew Shana2,Bestor David2,Cafarella Michael2,Gadepally Vijay2,Graefe Goetz3,Kepner Jeremy2,Kozyrakis Christos1,Kraska Tim2,Stonebraker Michael2,Suresh Lalith4,Zaharia Matei1

Affiliation:

1. Stanford

2. MIT

3. Google

4. VMware

Abstract

This paper lays out the rationale for building a completely new operating system (OS) stack. Rather than build on a single node OS together with separate cluster schedulers, distributed filesystems, and network managers, we argue that a distributed transactional DBMS should be the basis for a scalable cluster OS. We show herein that such a database OS (DBOS) can do scheduling, file management, and inter-process communication with competitive performance to existing systems. In addition, significantly better analytics can be provided as well as a dramatic reduction in code complexity through implementing OS services as standard database queries, while implementing low-latency transactions and high availability only once.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Reference52 articles.

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3. Transactional Python for Durable Machine Learning: Vision, Challenges, and Feasibility;Proceedings of the Seventh Workshop on Data Management for End-to-End Machine Learning;2023-06-18

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