Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/7765
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dc.contributor.authorRibarski, Pancheen_US
dc.contributor.authorIlijoski, Bojanen_US
dc.contributor.authorTojtovska, Biljanaen_US
dc.date.accessioned2020-04-26T06:17:01Z-
dc.date.available2020-04-26T06:17:01Z-
dc.date.issued2019-
dc.identifier.citationP. Ribarski, B. Ilijoski, B. Tojtovska, Comparing Databases for Inserting and Querying Jsons for Big Data, In: Gievska S., Madjarov G. (eds) ICT Innovations 2019. Big Data Processing and Mining. ICT Innovations 2019. Communications in Computer and Information Science, web proceedings.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12188/7765-
dc.description.abstractThis paper tackles the topic of performance in Big Data data ingestion, data querying and data analytics. We test the import of the Last.fm Million Song Dataset in Cassandra, Mongo, PostgreSQL, CockroachDB, Mariadb and Elasticsearch. We also test three types of queries over the JSON documents and present the test results for unique visibility in the direct comparison of the performance of the selected databases. We conclude that by using a combination of state of the art scalable database, for which we recommend Cassandra, and Elasticsearch for search and analytics, we can get a unique tool for efficiently storing and querying data which can schema easily along the way.en_US
dc.language.isoenen_US
dc.subjectBig Data, analytics, performanse, Elasticsearch, Cassandra, MongoDB, PostgreSQL, MariaDB, CockroachDM, JSONen_US
dc.titleComparing Databases for Inserting and Querying Jsons for Big Dataen_US
dc.typeArticleen_US
dc.relation.conferenceICT Innovations 2019en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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