Cite this DOI

Dr.Syed Abdul Sattar, D. A. S. (2023). Emerging Databases for Next Generation Big Data Applications. *Journal of Science & Technology*, *7*(1), 111–120. https://doi.org/10.46243/jst.2022.v7.i01.pp111-120

@article{drsyedabdulsattar2023emerging,
  author    = {Dr.Syed Abdul Sattar, Dr.Syed Abdul Sattar},
  title     = {{Emerging Databases for Next Generation Big Data Applications}},
  journal   = {Journal of Science \& Technology},
  year      = {2023},
  month     = {jul},
  volume    = {7},
  number    = {1},
  pages     = {111--120},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2022.v7.i01.pp111-120},
  url       = {https://doi.org/10.46243/jst.2022.v7.i01.pp111-120},
  language  = {en},
  abstract  = {The rising quality of large -scale period analytics applications (real -time inventory/pricing, mobile apps that offer you suggestions, fraud detection, risk analysis, etc.) emphases the requirement for distributed knowledge management systems which will handle quick transactions and analytics simultaneously. Efficient process of transactional and analytical requests, however, need completely different optimizations and branch of knowledge selections in a system. This paper presents the wildfire system that targets Hybrid Transactional and Analytical process (HTAP). wildfire leverages the Spark system to modify large -scale processing with differing types of complicated analytical requests, and columnar processing to modify quick transactions and analytics simultaneously}
}

TY  - JOUR
TI  - Emerging Databases for Next Generation Big Data Applications
AU  - Dr.Syed Abdul Sattar, Dr.Syed Abdul Sattar
JO  - Journal of Science & Technology
PY  - 2023
DA  - 2023/07/26/
VL  - 7
IS  - 1
SP  - 111
EP  - 120
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - The rising quality of large -scale period analytics applications (real -time inventory/pricing, mobile apps that offer you suggestions, fraud detection, risk analysis, etc.) emphases the requirement for distributed knowledge management systems which will handle quick transactions and analytics simultaneously. Efficient process of transactional and analytical requests, however, need completely different optimizations and branch of knowledge selections in a system. This paper presents the wildfire system that targets Hybrid Transactional and Analytical process (HTAP). wildfire leverages the Spark system to modify large -scale processing with differing types of complicated analytical requests, and columnar processing to modify quick transactions and analytics simultaneously
DO  - 10.46243/jst.2022.v7.i01.pp111-120
UR  - https://doi.org/10.46243/jst.2022.v7.i01.pp111-120
ER  -

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    "URL": "https://doi.org/10.46243/jst.2022.v7.i01.pp111-120",
    "title": "Emerging Databases for Next Generation Big Data Applications",
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    "abstract": "The rising quality of large -scale period analytics applications (real -time inventory/pricing, mobile apps that offer you suggestions, fraud detection, risk analysis, etc.) emphases the requirement for distributed knowledge management systems which will handle quick transactions and analytics simultaneously. Efficient process of transactional and analytical requests, however, need completely different optimizations and branch of knowledge selections in a system. This paper presents the wildfire system that targets Hybrid Transactional and Analytical process (HTAP). wildfire leverages the Spark system to modify large -scale processing with differing types of complicated analytical requests, and columnar processing to modify quick transactions and analytics simultaneously",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2022.v7.i01.pp111-120 gives all four in one JSON answer.