A Comparative Analysis of JSON Schema Inference Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457385" target="_blank" >RIV/00216208:11320/22:10457385 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.5220/0011046000003176" target="_blank" >https://doi.org/10.5220/0011046000003176</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0011046000003176" target="_blank" >10.5220/0011046000003176</a>
Alternative languages
Result language
angličtina
Original language name
A Comparative Analysis of JSON Schema Inference Algorithms
Original language description
NoSQL databases are becoming increasingly more popular due to their undeniable advantages in the context of storing and processing Big Data, mainly horizontal scalability and minimal requirement to define a schema upfront. In the absence of the explicit schema, however, an implicit schema inherent to the stored data still exists and it needs to be reverse engineered from the data. Once inferred, it is of a great value to the stake-holders and database maintainers. Nevertheless, the problem of schema inference is non-trivial and is still the subject of ongoing research. In this paper we provide a comparative analysis of five recent proposals of schema inference approaches targeting the JSON format. We provide both static and dynamic comparison of the approaches. In the former case we compare various features. In the latter case we involve both functional and performance analysis. Finally, we discuss remaining challenges and open problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA20-22276S" target="_blank" >GA20-22276S: Unified Management of Multi-Model Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ENASE: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING
ISBN
978-989-758-568-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
379-386
Publisher name
SCITEPRESS
Place of publication
SETUBAL
Event location
Virtual Event
Event date
Apr 25, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000814765400037