{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T03:16:43Z","timestamp":1758079003799,"version":"3.44.0"},"reference-count":5,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:p>Relational databases are great for data analysis and exploration, but require a carefully crafted schema, which causes high manual overhead. Moreover, entities not considered during schema design cannot be stored. In contrast, schemaless approaches allow users to store all kinds of data without the need for a schema, but require schema-checking on read to ensure that queries can read certain attributes. We therefore advocate for a new class of database systems that organize the data in a schema autonomously when it is inserted schemalessly by users. Such databases should thus be able to store data semantically meaningful but without requiring the user to design a schema, neither upfront during setup nor when an insert is executed. In this demo, we showcase JUSTINE, which is a first implementation of this new class of database systems that can automatically adjust a database schema based on input queries. Our showcase features both (1) an interactive mode where attendees can enter their own data as well as (2) the execution of a full workload where users can see how the database schema evolves during batch execution. The workload can be customized by changing different parameters.<\/jats:p>","DOI":"10.14778\/3750601.3750652","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:38:05Z","timestamp":1758029885000},"page":"5283-5286","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["JUSTINE (JUST-INsert Engine): Demonstrating Self-Organizing Data Schemas"],"prefix":"10.14778","volume":"18","author":[{"given":"Benjamin","family":"H\u00e4ttasch","sequence":"first","affiliation":[{"name":"DFKI &amp; TU Darmstadt, Germany"}]},{"given":"Leon","family":"Kr\u00fcger","sequence":"additional","affiliation":[{"name":"TU Darmstadt, Germany"}]},{"given":"Carsten","family":"Binnig","sequence":"additional","affiliation":[{"name":"TU Darmstadt &amp; DFKI, Germany"}]}],"member":"320","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"QLoRA: Efficient Finetuning of Quantized LLMs. arXiv preprint arXiv:2305.14314","author":"Dettmers Tim","year":"2023","unstructured":"Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023. QLoRA: Efficient Finetuning of Quantized LLMs. arXiv preprint arXiv:2305.14314 (2023)."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","unstructured":"Jinyang Li Binyuan Hui Ge Qu Binhua Li Jiaxi Yang Bowen Li Bailin Wang Bowen Qin Rongyu Cao Ruiying Geng Nan Huo Xuanhe Zhou Chenhao Ma Guoliang Li Kevin C. C. Chang Fei Huang Reynold Cheng and Yongbin Li. 2023. Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs. arXiv:2305.03111 [cs] 10.48550\/arXiv.2305.03111","DOI":"10.48550\/arXiv.2305.03111"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","unstructured":"Hugo Touvron Thibaut Lavril Gautier Izacard Xavier Martinet Marie-Anne Lachaux Timoth\u00e9e Lacroix Baptiste Rozi\u00e8re Naman Goyal Eric Hambro Faisal Azhar Aurelien Rodriguez Armand Joulin Edouard Grave and Guillaume Lample. 2023. LLaMA: Open and Efficient Foundation Language Models. arXiv:2302.13971 [cs] 10.48550\/arXiv.2302.13971","DOI":"10.48550\/arXiv.2302.13971"},{"key":"e_1_2_1_4_1","volume-title":"Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB","author":"Vogel Liane","year":"2023","unstructured":"Liane Vogel and Carsten Binnig. 2023. WikiDBs: A Corpus of Relational Databases From Wikidata. In Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28 - September 1, 2023 (CEUR Workshop Proceedings), Vol. 3462. CEUR-WS.org. https:\/\/ceur-ws.org\/Vol-3462\/TADA3.pdf"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1425"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3750601.3750652","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:44:04Z","timestamp":1758030244000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3750601.3750652"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":5,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["10.14778\/3750601.3750652"],"URL":"https:\/\/doi.org\/10.14778\/3750601.3750652","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2025,8]]},"assertion":[{"value":"2025-09-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}