Emerging Databases for Next Generation Big Data Applications
M. Sailaja1, V. Sundara Ratnam2, N. Baby Rani3
1M. Sailaja, Assistant Professor, Department of Computer Science and Engineering, MRECW, Hyderabad (Telangana), India.
2V. Sundara Ratnam, Professor, Department of Computer Science and Engineering, MRECW, Hyderabad (Telangana), India.
3N. Baby Rani, Assistant Professor, Department of Information Technology, MRECW, Hyderabad (Telangana), India.
Manuscript received on 15 December 2019 | Revised Manuscript received on 22 December 2019 | Manuscript Published on 31 December 2019 | PP: 182-189 | Volume-9 Issue-1S6 December 2019 | Retrieval Number: A10371291S619/19©BEIESP | DOI: 10.35940/ijeat.A1037.1291S619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This raised as quality into large scale periods into analytic application as real time inventor of pricing, mobile application in that offers we suggestion, fraud detections, risks as analyzed, etc. emphasis in the requirements with distributes knowledge’s management systems in which is into handle quickly transactions & analytics simultaneous. Efficiently into processes into transactions & analytically as requested, though, needed as complete into various optimization & branching into knowledge selection as a systems. In the paper presented in the wildfire systems in that target Hybrid Transactional & Analytical process (HTAP). This wildfire leverage in the Spark systems into modified as large scale process for different types as the difficult analytical request, & columnar process to modify as quick transaction & analytics simultaneous.
Keywords: Big Data, HTAP.
Scope of the Article: Big Data Security