News & Events
[DB Seminar] Spring 2018: Joy Arulraj
For the first time since Von Neumann's architecture of the 1940s, device manufacturers have created a new non-volatile memory (NVM) technology that can serve as both system memory and storage. NVM supports low-latency byte-addressable reads and writes similar to volatile memory, but all writes to it are persistent like a solid-state disk. The advent of NVM invalidates decades of design decisions that are deeply embedded in today's database systems. These systems are unable to take full advantage of NVM because Read More
[DB Seminar] Fall 2017: Barry Morris (NuoDB)
For decades the industry has sought solutions to the challenge of efficient distributed transactions, and ideally to elastically-scalable distributed transactions. The opportunity for such systems is to provide on-demand capacity, redundancy-based uptime models, and automation of labor-intensive administrative tasks. Additionally Elastic SQL systems may provide a route to geo-distributed transactions processing. The approaches to this challenge have all involved very significant trade-offs, and in general they have historically not been widely adopted. Current approaches to Elastic SQL include two-phase commit Read More
[DB Seminar] Fall 2017: Joy Arulraj
For the first time in 25 years, a new non-volatile memory (NVM) category is being created that is two orders of magnitude faster than current durable storage devices. The advent of NVM fundamentally changes the dichotomy between memory and durable storage in database systems. These new NVM devices are almost as fast as DRAM, but all writes to it are potentially persistent even after power loss. Existing database systems are unable to take full advantage of this technology because their Read More
Summer 2018 Research Internships
The Carnegie Mellon Database Group is offering multiple internship positions for a special summer research project at its Pittsburgh, Pennsylvania campus. It will be an intense 12-week internship from June to August 2018. The project will be to work on a new open-source distributed database system from scratch. Thus, we are looking for candidates that have strong systems-level C/C++ programming skills. Interns will be paid a three-month summer salary (commensurate with skills and experience) and the cost of travel expenses. Read More
[DB Seminar] Fall 2017: Capstone Project Practice Talks
Five of the DB group's Masters students will present their Capstone Projects: Building in-memory DBMS cost model in Peloton (Shuyao Bi) Extend Query Optimizer in Peloton (Patrick Huang) Robust Hash Join Execution (Chen Luo) JIT Compilation of User-Defined Functions in High Performance Database Management Systems (Prashasthi Prabhakar) ART index and index scan code gen (Min Huang) Read More
[Fall 2017] Peloton Hack-a-thon
The CMU Database Group is holding an all day programming session for the Peloton database system project. The goal of this event is to provide an introduction to the system and teach students how to get started with the project. The day will begin with an overview of the system and build/test it. We will then teach everyone how to write a new built-in SQL function (e.g., string functions). Attendees will divide up into small groups and work together to Read More
Alex Benik (Battery Ventures)
Alex Benik is a Partner at Battery Ventures. The talk promises to be buzzword- and jargon-fueled romp through current topics in venture capital. Alex will review some of the basics of the venture-capital industry and cover a number of areas Battery is focused on in its practice investing across enterprise IT and developer tools/platforms. He will also provide some advice for technical founders looking to become entrepreneurs, and pass on some pearls of wisdom from CMU grads in the Battery Read More
[Time Series Database Lectures] Michael Freedman (TimescaleDB/Princeton)
Time-series data is now everywhere—IoT, user event streams, system monitoring, finance, adtech, industrial control, transportation, and logistics—and increasingly used to power core applications. It also creates a number of technical challenges: to ingest high volumes of structured data; to ask complex, performant queries for both recent and historical time intervals; to perform specialized time-centric analysis and data management. And this data doesn’t exist in isolation, entries must often be joined against other relational data to ask key business questions (e.g., Read More
Shasank Chavan (Oracle)
Analytic workloads in data management systems are dominated by joins, aggregations, scan and filtering costs. In-Memory columnar databases have significantly optimized scans using compressed data formats and SIMD vectorization techniques, but have made little impact to the rest of the query execution plan. The Oracle Database In-Memory (DBIM) Option introduced new SQL execution operators that accelerate a wide range of analytic queries by optimizing aggregation over joins for star and similar schemas. Group-by expressions are pushed down into the scans Read More