News & Events
Building Novel Abstractions for a Declarative Cloud (Tianyu Li)
As the cloud evolves in capability, it has also become increasingly complex and difficult to program. New abstractions are necessary to ensure next-generation cloud applications are correct, simple, and efficient. In this talk, I will first describe Resilient Composition, a new abstraction that ensures fault-tolerance in applications composed from independent, distributed components. The key insight is to rely on atomic, fault-tolerant “steps” that span component operations and messages. I will present DARQ, an efficient execution engine for such steps, and Read More
Redesigning Blockchains: SSD-optimized Verifiable Databases and Beyond (Daniel Lin-Kit Wong)
Blockchains are decentralized ledgers that replace trusted central authorities with verifiable distributed consensus. This decentralization has resulted in blockchains effectively becoming ‘slow and expensive computers’, but there are huge opportunities for architectural optimization across the entire blockchain software stack. We begin this talk by outlining the scaling challenges from a systems researcher’s perspective, and discussing the bottlenecks faced in computation, storage, and network bandwidth. We then discuss how we optimized the blockchain storage layer using our novel verifiable database, the Read More
SQL or Death? Seminar Series – Spring 2025
Pittsburgh, PA — The Carnegie Mellon University Database Research Group is pleased to announce its wildest seminar series yet starting February 2025. “SQL or Death?” is no-holds-barred exploration of replacements for SQL and techniques to make SQL even better than it is. The schedule features legendary database researchers and industry stalwarts. Each session will challenge conventional wisdom with the kind of intensity that makes even seasoned DBAs break into a cold sweat. Even the late, great Ol’ Dirty Bastard (ODB) Read More
[SQL Death] EdgeQL with Gel
This talk is part of the SQL or Death? Seminar Series. Zoom Link: https://cmu.zoom.us/j/93441451665 (Passcode 261758) Read More
[SQL Death] MariaDB’s New Query Optimizer
This talk is part of the SQL or Death? Seminar Series. Zoom Link: https://cmu.zoom.us/j/93441451665 (Passcode 261758) Read More
[SQL Death] OxQL: Oximeter Query Language
This talk is part of the SQL or Death? Seminar Series. Zoom Link: https://cmu.zoom.us/j/93441451665 (Passcode 261758) Read More
[SQL Death] StarRocks Query Optimizer
StarRocks is a C++ analytical database that handles large-scale, high-concurrency, low-latency OLAP queries. In this presentation, Kaisen Kang, Tech Lead of the StarRocks Query Team, will provide an in-depth look at the StarRocks optimizer, the key optimizations, and design choices. The talk will focus on two key areas: Key Optimizations – A deep dive into three representative optimizations: Multi-left join colocate optimization, Partitioned Materialized Views auto union rewrite, and Low Cardinality global dictionary optimization, showcasing how they enhance query performance. Read More
[SQL Death] PRQL: Pipelined Relational Query Language
This talk is part of the SQL or Death? Seminar Series. Zoom Link: https://cmu.zoom.us/j/93441451665 (Passcode 261758) Read More
[SQL Death] Pipe Syntax in SQL: SQL for the 21st Century
SQL has been extremely successful as the de facto standard language for working with data. Virtually all mainstream database-like systems use SQL as their primary query language. But SQL is an old language with significant design problems, making it difficult to learn, difficult to use, and difficult to extend. Many have observed these challenges with SQL, and proposed solutions involving new languages. New language adoption is a significant obstacle for users, and none of the potential replacements have been successful Read More
[SQL Death] Malloy: A Modern Open Source Language for Analyzing, Transforming, and Modeling Data
In software we express our ideas through tools. In data, those tools think in rectangles. From spreadsheets to the data warehouses, to do any analytical calculation, you must first go through a rectangle.. Forcing data through a rectangle shapes the way we solve problems (for example, dimensional fact tables, OLAP Cubes). But really, most Data isn’t rectangular. Most data exists in hierarchies (orders, items, products, users). Most query results are better returned as a hierarchy (category, brand, product). Can we Read More