Graph Database Quotes

The Deliverator had to borrow some money to pay for it. Had to borrow it from the Mafia, in fact. So he's in their database now—retinal patterns, DNA, voice graph, fingerprints, footprints, palm prints, wrist prints, every fucking part of the body that had wrinkles on it—almost—those bastards rolled in ink and made a print and digitized it into their computer.

Different databases are designed to solve different problems. Using a single database engine for all of the requirements usually leads to non- performant solutions; storing transactional data, caching session information, traversing graph of customers and the products their friends bought are essentially different problems.

Historically, data started out being represented as one big tree (the hierarchical model), but that wasn’t good for representing many-to-many relationships, so the relational model was invented to solve that problem. More recently, developers found that some applications don’t fit well in the relational model either. New nonrelational “NoSQL” datastores have diverged in two main directions: Document databases target use cases where data comes in self-contained documents and relationships between one document and another are rare. Graph databases go in the opposite direction, targeting use cases where anything is potentially related to everything.

All three models (document, relational, and graph) are widely used today, and each is good in its respective domain. One model can be emulated in terms of another model—for example, graph data can be represented in a relational database—but the result is often awkward. That’s why we have different systems for different purposes, not a single one-size-fits-all solution.

There are also books that contain collections of papers or chapters on particular aspects of knowledge discovery—for example, Relational Data Mining edited by Dzeroski and Lavrac [De01]; Mining Graph Data edited by Cook and Holder [CH07]; Data Streams: Models and Algorithms edited by Aggarwal [Agg06]; Next Generation of Data Mining edited by Kargupta, Han, Yu, et al. [KHY+08]; Multimedia Data Mining: A Systematic Introduction to Concepts and Theory edited by Z. Zhang and R. Zhang [ZZ09]; Geographic Data Mining and Knowledge Discovery edited by Miller and Han [MH09]; and Link Mining: Models, Algorithms and Applications edited by Yu, Han, and Faloutsos [YHF10]. There are many tutorial notes on data mining in major databases, data mining, machine learning, statistics, and Web technology conferences.

Got himself fired for pulling a sword on an acknowledged perp. Slid it right through the fabric of the perp’s shirt, gliding the flat of the blade along the base of his neck, and pinned him to a warped and bubbled expanse of vinyl siding on the wall of the house that the perp was trying to break into. Thought it was a pretty righteous bust. But they fired him anyway because the perp turned out to be the son of the vice-chancellor of the Farms of Merryvale. Oh, the weasels had an excuse: said that a thirty-six-inch samurai sword was not on their Weapons Protocol. Said that he had violated the SPAC, the Suspected Perpetrator Apprehension Code. Said that the perp had suffered psychological trauma. He was afraid of butter knives now; he had to spread his jelly with the back of a teaspoon. They said that he had exposed them to liability. The Deliverator had to borrow some money to pay for it. Had to borrow it from the Mafia, in fact. So he’s in their database now—retinal patterns, DNA, voice graph, fingerprints, footprints, palm prints, wrist prints, every fucking part of the body that had wrinkles on it—almost—those bastards rolled in ink and made a print and digitized it into their computer. But it’s their money—sure they’re careful about loaning it out. And when he applied for the Deliverator job they were happy to take him, because they knew him. When he got the loan, he had to deal personally with the assistant vice-capo of the Valley, who later recommended him for the Deliverator job. So it was like being in a family. A really scary, twisted, abusive family. CosaNostra

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So he’s in their database now—retinal patterns, DNA, voice graph, fingerprints, footprints, palm prints, wrist prints, every fucking part of the body that had wrinkles on it—almost—those bastards rolled in ink and made a print and digitized it into their computer.