Tackling Challenges in Implementing Large-Scale Graph Databases.
Graph databases (GDBs) have become increasingly important for managing large repositories of unstructured information, particularly due to their ability to represent complex relationships between entities. While their expressive data models and flexible query languages drive their success, the prima...
| Publicado en: | Communications of the ACM Vol. 67; no. 8; pp. 40 - 45 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Association for Computing Machinery
Aug2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=178779533&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 178779533 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Aug2024 vid: 67 iid: 8 pid: 68 pub: Association for Computing Machinery artinfo: ui: 178779533 10.1145/3653314 ppf: 40 ppct: 5 formats: tig: atl: Tackling Challenges in Implementing Large-Scale Graph Databases. aug: au: Arroyuelo, Diego Hogan, Aidan Navarro, Gonzalo Reutter, Juan Vrgoč, Domagoj affil: Pontificia Universidad Católica, Chile University of Chile su: Graph algorithms Databases Query languages (Computer science) Data structures Relational databases Data modeling sug: subj: Graph algorithms Databases Query languages (Computer science) Data structures Relational databases Data modeling ab: Graph databases (GDBs) have become increasingly important for managing large repositories of unstructured information, particularly due to their ability to represent complex relationships between entities. While their expressive data models and flexible query languages drive their success, the primary challenge hindering wider adoption is the efficiency of their implementation. In response to these challenges, significant research efforts, particularly in Latin America, focus on developing new data models, query languages, and efficient algorithms, including space-efficient structures like the Ring index, which supports complex queries with minimal memory footprint. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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