prikaz prve stranice dokumenta Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari
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master's thesis
Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:694017
Slatinac, Mario
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Slatinac, M. (2019). Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:694017

Slatinac, Mario. "Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:694017

Slatinac, Mario. "Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:694017

Slatinac, M. (2019). 'Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 30 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:694017

Slatinac M. Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 December 30] Available at: https://urn.nsk.hr/urn:nbn:hr:168:694017

M. Slatinac, "Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:694017

Metadata
TitlePrimjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari
Title (english)Time Series Databases Application in the Internet of Things
AuthorMario Slatinac
MentorMario Kušek (mentor)
Committee memberMario Kušek (predsjednik povjerenstva)
Committee memberJurica Babić (član povjerenstva)
Committee memberKrešimir Pripužić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Primjena baza podataka zasnovanih na vremenskim sljedovima u Internetu stvari sve je popularnija zbog specijalizirane primjene takvih baza podataka na vremensko slijedne podatke koji dolaze iz Interneta stvari. Među vremensko slijednim bazama podataka istaknule su se baze podataka InfluxDB i TimescaleDB koja je proširenje na bazu podataka PostgreSQL. Prednost vremensko slijednih baza podataka nad NoSQL i relacijskim bazama podataka je u visokim performancama, funkcijama namijenjenim za obradu i upravljanje vremensko slijednim podacima kao što su kontinuirani upiti koji se periodično i automatski izvode nad podacima koji pristižu u stvarnom vremenu i čiji se rezultat pohranjuje u bazu podataka. Korištenjem alata Time Series Benchmark Suite provedeno je testiranje performanci unosa podataka s obzirom na veličinu grupe podataka i kardinalnost skupa podataka za bazu podataka InfluxDB i TimescaleDB. Rezultati testiranja pokazali su da baza podataka InfluxDB ima manje vrijeme izvođenja od baze podatka TimescaleDB s povećanjem veličine grupe. Oba dvije baze podataka pokazuju povećanje vremena unosa podataka s povećanjem kardinalnosti skupa podataka. Baza podataka InfluxDB u oba dva testna scenarija pokazuje visoku potrošnju računalnih resursa, odnosno procesora i radne memorije dok kod baze podataka TimescaleDB to nije slučaj.
Abstract (english)
The application of time series databases on the Internet of things is increasingly popular because of the specialized use of such databases to time series data coming from the Internet of things. Among the time series databases, InfuxDB and TimescaleDB databases have pointed out, where TimescaleDB is an extension for the PostgreSQL database. The advantage of time series databases over NoSQL and relational databases is in high performance, functions designed for aggregating and managing time series data such as continuous queries that are periodically and automatically executed over real-time data and whose result is stored in the database. By using the Time Series Benchmark Suite tool, performance of data ingest were tested with different batch size and different cardinality of data set for InfluxDB and TimescaleDB database. Test results have shown that the InfluxDB database needs less time to ingest data than the TimescaleDB database when batch size is increasing. Both databases show increased data ingest time by growing cardinality for the dataset. The InfluxDB database in both test scenarios shows the high usage of CPU and random-access memory (RAM), where for the TimescaleDB it is not the case.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:694017
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2020-01-07 22:03:14