[Fall 2023] Viewing Collaborative Editing Through a Databases Lens (Martin Kleppmann) CANCELLED
Software that allows several users to collaboratively edit a document, such as Google Docs, has traditionally been ignored by the databases community. This is surprising, because managing the edits to a text document, spreadsheet, vector graphics file, etc. is very much a data management problem, albeit with a data model that is very different from that supported by most databases. Collaboration software needs replication, concurrency control, and data layouts for efficient storage and retrieval. In our work on Automerge, a... Read More
[ML⇄DB 2023] OtterTune: AI-Powered Database Optimization as a Service! (Dana Van Aken)
This talk is part of the ML⇄DB Seminar Series. Zoom Link: https://cmu.zoom.us/j/91461275681 (Passcode 177332) Read More
[ML⇄DB 2023] Qdrant: Vector Search Engine Internals (Andrey Vasnetsov)
This talk is part of the ML⇄DB Seminar Series. Zoom Link: https://cmu.zoom.us/j/91461275681 (Passcode 177332) Read More
[Fall 2023] New Semester Research Meeting
Carnegie Mellon University's renowned Database Group is thrilled to announce the kickoff of its Fall 2023 semester with a highly anticipated meeting on Thursday, August 31st. This gathering promises to be an extraordinary occasion as the members embark on a vainglorious retrospective, celebrating the group's remarkable research achievements over the years, as well as to begin discussions on new projects. As pioneers in the field of database systems and data management, the Database Group at Carnegie Mellon University has consistently... Read More
On Embedding Database Management System Logic in Operating Systems via Restricted Programming Environments (Matt Butrovich)
The rise in computer storage and network performance means that disk I/O and network communication are often no longer bottlenecks in database management systems (DBMSs). Instead, the overheads associated with operating system (OS) services (e.g., system calls, thread scheduling, and data movement from kernel- space) limit query processing responsiveness. To avoid these overheads, user-space applications prioritizing performance over simplicity can elide these software layers with a kernel-bypass design. However, extracting benefits from kernel-bypass frameworks is challenging, and the libraries are... Read More
[Summer 2023] Towards a Hardware-software Approach for High-performance Databases (Jignesh Patel)
In various industries, in-database analytics are crucial for decision-making. Yet, the growing amount of data presents challenges as traditional methods become excessively time-consuming and costly. Moore's Law and Dennard scaling, which previously aided data-intensive analytics, are reaching their physical limits. A new approach is needed to handle analytics workloads. The speed gap between processing units and memory creates bottlenecks for analytics workloads (the classic von Neumann bottleneck). Our approach involves using “intelligent” memory that can compute results alongside the stored... Read More
[Spring 2023] 15-721 Final Project Presentations
Carnegie Mellon University is thrilled to announce the upcoming final project presentations for the Advanced Database Systems course for the Spring 2023 semester. This eagerly awaited event showcases the hard work and innovation of the university's talented students as they present their cutting-edge projects to an audience of esteemed guests and fellow students. The presentations promise to deliver captivating insights into the future of database systems. CMU's Advanced Database Systems course, renowned for its comprehensive curriculum and focus on industry-relevant... Read More
Return of the Database Machines? Towards a Hardware-Software Approach for High-performance Databases (Jignesh Patel)
Analytic database applications have an insatiable appetite for higher performance. In the past, a large part of this appetite was met by leveraging the gift of Moore’s Law. However, the slowing down of Moore’s Law now requires a new approach. Fortunately, the hardware landscape is currently undergoing a Cambrian explosion of new architectures. In this talk, I will describe how one class of architecture may provide part of the answer to our search for future high-performance database systems. This architecture... Read More
MS Thesis Defense: High Performance DBMS Design for Intelligent Query Scheduling (Deepayan Patra)
Decades of research in the field of database management systems (DBMSs) have focused on improving system performance with impressive results. Modern analytical databases take advantage of innovative methods such as vectorization and compilation to improve single query performance, use supporting data structures such as indexes or views to reduce data access requirements, and support the execution of multiple queries in parallel while maintaining necessary isolation guarantees. We propose a new line of work with workload and architecture-aware scheduling algorithms to... Read More