Subject: Big Data, analytics, performanse, Elasticsearch, Cassandra, MongoDB, PostgreSQL, MariaDB, CockroachDM, JSON
Year: 2019
Type: Article
Title: Comparing Databases for Inserting and Querying Jsons for Big Data
Author: Ribarski, Panche
Author: Ilijoski, Bojan
Author: Tojtovska, Biljana
Abstract: This 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.
Publisher:
Relation: ICT Innovations 2019
Identifier: oai:repository.ukim.mk:20.500.12188/7765
Identifier: P. 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.
Identifier: http://hdl.handle.net/20.500.12188/7765
