An adaptive spark-based framework for querying large-scale NoSQL and relational databases.
The growing popularity of big data analysis and cloud computing has created new big data management standards. Sometimes, programmers may interact with a number of heterogeneous data stores depending on the information they are responsible for: SQL and NoSQL data stores. Interacting with heterogeneo...
Saved in:
Main Authors: | Eman Khashan, Ali Eldesouky, Sally Elghamrawy |
---|---|
Format: | article |
Language: | EN |
Published: |
Public Library of Science (PLoS)
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/3cacfe4d48c44ca29d55082256e8a7ed |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Layanan Cloud Computing untuk Mendukung Kinerja Administrasi Database Tanpa Menggunakan Perintah SQL
by: Hero Wintolo, et al.
Published: (2020) -
Translating synthetic natural language to database queries with a polyglot deep learning framework
by: Adrián Bazaga, et al.
Published: (2021) -
A Selected Deep Learning Cancer Prediction Framework
by: Nadia G. Elseddeq, et al.
Published: (2021) -
Efficient Group <i>K</i> Nearest-Neighbor Spatial Query Processing in Apache Spark
by: Panagiotis Moutafis, et al.
Published: (2021) -
recount3: summaries and queries for large-scale RNA-seq expression and splicing
by: Christopher Wilks, et al.
Published: (2021)