data modeling

The first lecture of Andy Pavlo's CMU 15-445 Intro to Database Systems (Fall 2019), covering course introduction and the relational model.

Database pioneer Michael Stonebraker argues that 'big data' is really at least four different problems: big volumes with small analytics, big analytics, velocity, and variety. He comments on where each market is heading.

Rich Hickey, creator of Clojure and designer of Datomic, gives a JaxConf 2012 talk that takes apart traditional database architecture. He presents a different way to think about databases and explains the reasoning behind Datomic's fact-based design.

Jon Gjengset's 2020 PhD dissertation presentation at MIT on partial state in dataflow-based materialized views, the idea behind the Noria database. The Q&A is cut out.

Linus Tech Tips documents a major RAID failure on its Whonnock server and the attempt to recover the lost data with a data recovery firm.

AWS's short promo for Snowmobile, a 45-foot shipping container pulled by a semi truck that moves up to 100PB of data to AWS.

A five-minute excerpt of Rich Hickey's Clojure Made Simple talk, with new slides, ranting about HttpServletRequest and specificity. He argues for using generic maps instead of many specific classes and getters.

Kevin Fang comically retells GitLab's 2017 incident in which an engineer deleted the production database, based on the company's postmortems. It walks through the confusion and failed backups.

Fox Business interview in which Oracle co-founder Larry Ellison claims Oracle will beat Amazon at cloud databases. He argues the world's valuable data lives in Oracle and says Amazon struggled to move off it.

Peter Norvig's UBC distinguished lecture on how massive amounts of simple data, such as for language modeling, can yield understanding that hand-built models could not.

Martin Kleppmann argues that databases are global shared mutable state and proposes treating them as an ever-growing log of immutable facts. Derived data such as caches, indexes and views is then built by stream processors like Apache Samza. The talk draws on Kafka and LinkedIn's experience with commit logs.

Avi Bryant demos Dabble DB, a web-based spreadsheet-like database for building apps without code. It shows how users can model and relate data through a smooth interface.

Michael Arntzenius's Strange Loop talk on Datafun, a functional query language that brings database-style querying into a general-purpose language. It discusses bridging database theory and programming languages.

A guest lecture Jon Gjengset gave at Two Sigma on using Rust for large, high-performance systems. It covers why Rust suits such projects, the Noria research database, a concurrent data structure used in it, and practical experience.

Martin Kleppmann's Kafka Summit 2018 keynote asks whether Kafka can be considered a database. He covers event logs and related data-systems ideas.

James Powell's nearly two-hour PyData talk builds up Python's data model, decorators, generators and context managers, coding live in Vim. It aims to take intermediate programmers toward real Python expertise.

Richard Feldman's elm-conf talk on designing models so that bugs from impossible application states cannot occur, using Elm's compiler and types. It demonstrates techniques for making invalid states unrepresentable.

Mike Acton of Insomniac Games argues that a program's purpose is transforming data, and shows how common C++ approaches work against that in performance-critical game development. He covers cache behavior, data layout and the limits of compilers.

Juan Pedro Bolivar Puente explains immutable and persistent data structures in C++ and how they support value semantics. He presents the Immer library, rrb-trees, and a prototype text editor that opens a huge file instantly.

A five-minute lightning demo of VisiData, a terminal tool for exploring and manipulating data. It uses two months of NYC 311 complaint data to drill down, plot points on a virtual map and save selected rows.

John Oliver's Last Week Tonight segment explains how data brokers collect and sell personal information, including a stunt in which his team bought data to identify members of Congress.

Lee Byron of Facebook explains how persistent immutable data structures work and how to use them in React apps with Immutable.js. He covers memoization benefits and avoiding coupling through shared mutable state.

Benn Jordan investigates infrasound and low-frequency noise from data centers, including xAI's Colossus and a crypto mine, and reports his own experiments on the effects. The video covers the health and community impacts on nearby residents.

Peter Norvig's 2007 Google talk on theorizing from data, covering what huge datasets can do for language understanding, translation, information extraction and inference. It argues that more data often beats cleverer models.

A Business Insider investigation into the US boom in AI data centers, mapping where they are, who owns them, and how much power and water they consume. It looks at the costs borne by communities, with a focus on Virginia.

Eager Space examines the practicality of putting data centers in orbit, walking through three scenarios with cost calculations and the launch cost reductions that would be required.

John Ousterhout's Netdev 0x16 keynote arguing that nearly every aspect of TCP is wrong for the datacenter, from connections and streams to reliable delivery and congestion control. He presents the case for a replacement protocol.

Tantacrul examines sonification, the practice of turning data into sound or music, and critiques how scientists and musicians, including NASA and CERN projects, use it well and poorly.

Scott Manley examines why SpaceX, Google and others are looking at orbital data centers. He walks through the economics, heat rejection and solar power arguments, with links to the Lumen/Starcloud and Google Suncatcher papers.

Scott Manley explains the thermal balance of spacecraft and how a satellite could be configured to radiate away the heat from datacenter-scale computing in space. His rough numbers suggest it is feasible.

Raymond Hettinger explains Python's dataclasses module, showing the problem it solves and its key design decisions. He places it in a progression from tuples and dicts through named tuples and attrs.

Scott Manley analyzes the idea of putting data centers in orbit, prompted by Lumen Orbit's funding. He examines the claimed advantage of constant solar power against launch cost, cooling and mass.

Edward Kmett's 2013 talk at Prezi in Budapest on succinct data structures, which store data in close to the information-theoretic minimum space while supporting fast queries. It ties together the research and walks through his Haskell succinct library.

James Hamilton of AWS gives a Velocity 2010 keynote on datacenter infrastructure innovation, focused on power and cooling costs and a breakdown of where datacenter spending goes.

An LGR Oddware episode looking at Sony's MDH-10 MD Data drive from 1995, which used MiniDisc for computer storage years before Hi-MD. The host tries out the drive with its original drivers and software.

Joe Kava, VP of Google's Data Center Operations, gives a short tour of a Google data center. He covers security, sustainability and the core infrastructure architecture.

Mark Raasveldt of CWI presents DuckDB, an embeddable analytical database described as the SQLite for analytics, in a CMU Database Group talk. He explains why it was built, what it is for, and how it works.

Rick Houlihan's AWS re:Invent 2018 deep dive on advanced DynamoDB design patterns. It covers index overloading, GSI sharding, composite keys, graph processing and transactions.

SQLite creator Richard Hipp gives a history of SQLite and explains where it shines as a database at the edge of the network with no DBA. He covers long-term support, testing and how it is used in products.

Lukas Eder's Devoxx talk on how modern cost-based SQL optimizers rewrite and plan queries in ways developers would not expect. It argues that declarative SQL, used well, can run complex queries very fast.