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The amount and the speed at which these environments produce and consume data are starting to challenge current spatial data management technologies. In this work, we report on our experience handling real-world spatiotemporal datasets: a stationary dataset referring to the parking monitoring system and a non-stationary dataset referring to a train-mounted railway monitoring system. In particular, we present the results of an empirical comparison of the retrieval performances achieved by three different off-the-shelf settings to manage spatiotemporal data, namely the well-established combination of <jats:italic>PostgreSQL<\/jats:italic> + <jats:italic>PostGIS<\/jats:italic> with standard indexing, a clustered version of the same setup, and then a combination of the basic setup with <jats:italic>Timescale<\/jats:italic>, a storage extension specialized in handling temporal data. Since the non-stationary dataset has put much pressure on the configurations above, we furtherly investigated the advantages achievable by combining the TSMS setup with state-of-the-art indexing techniques. Results showed that the standard indexing is by far outperformed by the other solutions, which have different trade-offs. This experience may help researchers and practitioners facing similar problems managing these types of data. \n<\/jats:p>","DOI":"10.1007\/s10115-023-02009-y","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T18:02:37Z","timestamp":1700503357000},"page":"2063-2088","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["How to manage massive spatiotemporal dataset from stationary and non-stationary sensors in commercial DBMS?"],"prefix":"10.1007","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0365-8575","authenticated-orcid":false,"given":"Vincenzo Norman","family":"Vitale","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1019-9004","authenticated-orcid":false,"given":"Sergio Di","family":"Martino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adriano","family":"Peron","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Massimiliano","family":"Russo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9680-3040","authenticated-orcid":false,"given":"Ermanno","family":"Battista","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,20]]},"reference":[{"issue":"5","key":"2009_CR1","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1109\/MWC.2016.7721736","volume":"23","author":"E Ahmed","year":"2016","unstructured":"Ahmed E, Yaqoob I, Gani A, Imran M, Guizani M (2016) Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges. 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