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Cauldron: A Scalable Domain Specific Database for Product Data
KTH, School of Information and Communication Technology (ICT).
2017 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This project investigated how NoSQL databases can be used together with a logical layer, instead of a relational database with separated backend logic, to search for products with customer specific constraints in an e-commerce scenario. The motivation behind moving from a relational database was the scalability issues and increased read latencies experienced as the data increased. The work resulted in a framework called Cauldron that uses pipelines a sequence of execution steps to expose its data stored in an in-memory key-value store and a document database. Cauldron uses write replication between distributed instances to increase read throughput at the cost of write latency. A product database with customer specific constraints was implemented using Cauldron to compare it against an existing solution based on a relational database. The new product database can serve search queries 10 times faster in the general case and up to 25 times faster in extreme cases compared to the existing solution.

Abstract [sv]

Projektet undersökte hur NoSQL databaser tillsammans med ett logiskt lager, istället för en relationsdatabas med separat backend logik, kan användas för att söka på produkter med kundunika restriktioner. Motivationen till att byta ut relationsdatabasen berodde på skalbarhetsproblem och långsammare svarstider när datamängden ökade. Arbetet resulterade i ett ramverk vid namn Cauldron som använder pipelines sammankopplade logiska steg för att exponera sin data från en minnesbunden nyckel-värde-databas och en dokumentdatabas. Cauldron använder replikering mellan distribuerade instanser för att öka läsgenomstömmningen på bekostnad av högre skrivlatenser. En produktdatabas med kundunika restriktioner implementerades med hjälp av Cauldron för att jämföra den mot en befintlig lösning baserad på en relationsdatabas. Den nya databasen kan besvara sökförfrågningar 10 gånger snabbare i normalfallen och upp till 25 gånger snabbare i extremfallen jämfört med den befintliga lösningen.

Place, publisher, year, edition, pages
2017. , p. 45
Series
TRITA-ICT-EX ; 2017:99
Keywords [en]
distributed systems, nosql, big data, e-commerce
Keywords [sv]
distributed systems, nosql, big data, e-commerce
National Category
Computer Sciences Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-215710OAI: oai:DiVA.org:kth-215710DiVA, id: diva2:1149081
Subject / course
Computer Science; Information Technology
Educational program
Master of Science - Software Engineering of Distributed Systems; Master of Science in Engineering - Information and Communication Technology
Supervisors
Examiners
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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