Rel: A Programming Language for Relational Data

  • Molham Aref
  • , Paolo Guagliardo
  • , George Kastrinis
  • , Leonid Libkin
  • , Victor Marsault
  • , Wim Martens
  • , Mary Mcgrath
  • , Filip Murlak
  • , Nathaniel Nystrom
  • , Liat Peterfreund
  • , Allison Rogers
  • , Cristina Sirangelo
  • , Domagoj Vrgoc
  • , David Zhao
  • , Abdul Zreika

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

From the moment of their inception, languages for relational data have been described as sublanguages embedded in a host programming language. Rel is a new relational language whose key design goal is to go beyond this paradigm with features that allow for programming in the large, making it possible to fully describe end to end application semantics. With the new approach we can model the semantics of entire enterprise applications relationally, which helps significantly reduce architecture complexity and avoid the well-known impedance mismatch problem. This paradigm shift is enabled by 50 years of database research, making it possible to revisit the sublanguage/host language paradigm, starting from the fundamental principles. We present the main features of Rel: those that give it the power to express traditional query language operations and those that are designed to grow the language and allow programming in the large.

Original languageEnglish
Title of host publicationSIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data
EditorsAmol Deshpande, Ashraf Aboulnaga, Babak Salimi, Badrish Chandramouli, Bill Howe, Boon Thau Loo, Boris Glavic, Carlo Curino, Daisy Zhe Wang, Dan Suciu, Daniel Abadi, Divesh Srivastava, Eugene Wu, Faisal Nawab, Ihab Ilyas, Jeffrey Naughton, Jennie Rogers, Jignesh Patel, Joy Arulraj, Jun Yang, Karima Echihabi, Kenneth Ross, Khuzaima Daudjee, Laks Lakshmanan, Minos Garofalakis, Mirek Riedewald, Mohamed Mokbel, Mourad Ouzzani, Oliver Kennedy, Oliver Kennedy, Paolo Papotti, Peter Alvaro, Peter Bailis, Renee Miller, Senjuti Basu Roy, Sergey Melnik, Stratos Idreos, Sudeepa Roy, Theodoros Rekatsinas, Viktor Leis, Wenchao Zhou, Wolfgang Gatterbauer, Zack Ives
PublisherAssociation for Computing Machinery
Pages283-296
Number of pages14
ISBN (Electronic)9798400715648
DOIs
StatePublished - 22 Jun 2025
Event2025 ACM SIGMOD/PODS International Conference on Management of Data, SIGMOD-Companion 2025 - Berlin, Germany
Duration: 22 Jun 202527 Jun 2025

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

Conference2025 ACM SIGMOD/PODS International Conference on Management of Data, SIGMOD-Companion 2025
Country/TerritoryGermany
CityBerlin
Period22/06/2527/06/25

Bibliographical note

Publisher Copyright:
© 2025 ACM.

Keywords

  • graph normal form
  • impedance mismatch
  • programming in the large
  • query language design
  • relational data model
  • relational knowledge graph
  • relational programming

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