Most database management systems cache pages from storage in a main memory buffer
pool. To do this, they either rely on a hash table that translates page identifiers into pointers …

In the dynamic landscape of technology, the convergence of Artificial Intelligence (AI) and
Operating Systems (OS) has emerged as a pivotal arena for innovation. Our exploration …

This paper revisits the H-Store/VoltDB concurrency control scheme for partitioned main-
memory databases, which we term run-to-completion-single-thread (RCST), with an eye …

Many cloud applications use both serverless functions, for bursts of stateless parallel
computation, and container orchestration, for long-running microservices and tasks that …

Data-intensive systems are the backbone of today's computing and are responsible for
shaping data centers. Over the years, cloud providers have relied on three principles to …

Providing strong fault-tolerant guarantees for the modern cloud is difficult, as application
developers must coordinate between independent stateful services and ephemeral compute …

This paper explores the intersection of operating systems and database systems, focusing
on the potential of specialized kernels for cloud-native database systems. Although the idea …

We present DBNet, a data-driven network automation framework built on top of a DBMS.
DBNet utilizes key primitives of a DBMS including tables, procedures, transactions, logging …

Cluster managers play a crucial role in data centers by distributing workloads among
infrastructure resources. Declarative Cluster Management (DCM) is a new cluster …

In machine learning (ML), Python serves as a convenient abstraction for working with key
libraries such as PyTorch, scikit-learn, and others. Unlike DBMS, however, Python …