NoSql Database Modeling Techniques and Fast Search of Enterprise Data
DOI:
https://doi.org/10.18034/ei.v10i1.671Keywords:
NoSQL, CRUD Operations, MongoDB, Cloud Database, Schema Modeling, Modeling Technique, Enterprise Content ManagementAbstract
There is a need for quick databases that can deal with enormous amounts of data because of the rapid growth of the Internet and the increase in the number of websites that allow users to develop their material, such as Facebook and Twitter. To accomplish this goal, new database management systems, which will be referred to collectively as NoSQL, are currently under development. Because there are various NoSQL databases, each with unique performance, it is essential to evaluate database performance. MongoDB, Cassandra, and Couchbase are the names of the three significant NoSQL databases considered for the performance evaluation. To investigate performance, a variety of workloads were developed. The read and update operations served as the basis for the evaluation that was carried out. The results of this study provide the ability to select the NoSQL database that best meets their requirements in terms of the particular mechanisms and applications.
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Amin, R., & Mandapuram, M. (2021). CMS - Intelligent Machine Translation with Adaptation and AI. ABC Journal of Advanced Research, 10(2), 199-206. https://doi.org/10.18034/abcjar.v10i2.693 DOI: https://doi.org/10.18034/abcjar.v10i2.693
Ballamudi, V. K. R. (2016). Utilization of Machine Learning in a Responsible Manner in the Healthcare Sector. Malaysian Journal of Medical and Biological Research, 3(2), 117-122. https://mjmbr.my/index.php/mjmbr/article/view/677
Ballamudi, V. K. R. (2019a). Artificial Intelligence: Implication on Management. Global Disclosure of Economics and Business, 8(2), 105-118. https://doi.org/10.18034/gdeb.v8i2.540 DOI: https://doi.org/10.18034/gdeb.v8i2.540
Ballamudi, V. K. R. (2019b). Road Accident Analysis and Prediction using Machine Learning Algorithmic Approaches. Asian Journal of Humanity, Art and Literature, 6(2), 185-192. https://doi.org/10.18034/ajhal.v6i2.529 DOI: https://doi.org/10.18034/ajhal.v6i2.529
Ballamudi, V. K. R. (2019c). Hybrid Automata: An Algorithmic Approach Behavioral Hybrid Systems. Asia Pacific Journal of Energy and Environment, 6(2), 83-90. https://doi.org/10.18034/apjee.v6i2.541 DOI: https://doi.org/10.18034/apjee.v6i2.541
Ballamudi, V. K. R. (2020). Militarization of Space. Asian Journal of Applied Science and Engineering, 9(1), 169–178. https://doi.org/10.18034/ajase.v9i1.38 DOI: https://doi.org/10.18034/ajase.v9i1.38
Ballamudi, V. K. R., & Desamsetti, H. (2017). Security and Privacy in Cloud Computing: Challenges and Opportunities. American Journal of Trade and Policy, 4(3), 129–136. https://doi.org/10.18034/ajtp.v4i3.667 DOI: https://doi.org/10.18034/ajtp.v4i3.667
Ballamudi, V. K. R., Lal, K., Desamsetti, H., & Dekkati, S. (2021). Getting Started Modern Web Development with Next.js: An Indispensable React Framework. Digitalization & Sustainability Review, 1(1), 1–11. https://upright.pub/index.php/dsr/article/view/83
Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2019). Voice Recognition Systems in the Cloud Networks: Has It Reached Its Full Potential?. Asian Journal of Applied Science and Engineering, 8(1), 51–60. https://doi.org/10.18034/ajase.v8i1.12 DOI: https://doi.org/10.18034/ajase.v8i1.12
Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2021). Algorithm Policy for the Authentication of Indirect Fingerprints Used in Cloud Computing. American Journal of Trade and Policy, 8(3), 231–238. https://doi.org/10.18034/ajtp.v8i3.651 DOI: https://doi.org/10.18034/ajtp.v8i3.651
Chen, S., Thaduri, U. R., & Ballamudi, V. K. R. (2019). Front-End Development in React: An Overview. Engineering International, 7(2), 117–126. https://doi.org/10.18034/ei.v7i2.662 DOI: https://doi.org/10.18034/ei.v7i2.662
Dai, C., Ye, Y., Liu, T. J., Zheng, J. J. (2013). Design of High Performance Cloud Storage Platform Based on Cheap PC Clusters Using MongoDB and Hadoop. Applied Mechanics and Materials, 380-384, 2050. https://doi.org/10.4028/www.scientific.net/AMM.380-384.2050 DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.2050
Dekkati, S., & Thaduri, U. R. (2017). Innovative Method for the Prediction of Software Defects Based on Class Imbalance Datasets. Technology & Management Review, 2, 1–5. https://upright.pub/index.php/tmr/article/view/78
Dekkati, S., Lal, K., & Desamsetti, H. (2019). React Native for Android: Cross-Platform Mobile Application Development. Global Disclosure of Economics and Business, 8(2), 153-164. https://doi.org/10.18034/gdeb.v8i2.696 DOI: https://doi.org/10.18034/gdeb.v8i2.696
Dekkati, S., Thaduri, U. R., & Lal, K. (2016). Business Value of Digitization: Curse or Blessing?. Global Disclosure of Economics and Business, 5(2), 133-138. https://doi.org/10.18034/gdeb.v5i2.702 DOI: https://doi.org/10.18034/gdeb.v5i2.702
Deming, C., Dekkati, S., & Desamsetti, H. (2018). Exploratory Data Analysis and Visualization for Business Analytics. Asian Journal of Applied Science and Engineering, 7(1), 93–100. https://doi.org/10.18034/ajase.v7i1.53 DOI: https://doi.org/10.18034/ajase.v7i1.53
Desamsetti, H. (2016a). A Fused Homomorphic Encryption Technique to Increase Secure Data Storage in Cloud Based Systems. The International Journal of Science & Technoledge, 4(10), 151-155.
Desamsetti, H. (2016b). Issues with the Cloud Computing Technology. International Research Journal of Engineering and Technology (IRJET), 3(5), 321-323.
Desamsetti, H. (2018). Internet of Things (IoT) Technology for Use as Part of the Development of Smart Home Systems. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 14–21. https://upright.pub/index.php/ijrstp/article/view/89
Desamsetti, H. (2020). Relational Database Management Systems in Business and Organization Strategies. Global Disclosure of Economics and Business, 9(2), 151-162. https://doi.org/10.18034/gdeb.v9i2.700 DOI: https://doi.org/10.18034/gdeb.v9i2.700
Desamsetti, H. (2021). Crime and Cybersecurity as Advanced Persistent Threat: A Constant E-Commerce Challenges. American Journal of Trade and Policy, 8(3), 239–246. https://doi.org/10.18034/ajtp.v8i3.666 DOI: https://doi.org/10.18034/ajtp.v8i3.666
Desamsetti, H., & Lal, K. (2019). Being a Realistic Master: Creating Props and Environments Design for AAA Games. Asian Journal of Humanity, Art and Literature, 6(2), 193-202. https://doi.org/10.18034/ajhal.v6i2.701 DOI: https://doi.org/10.18034/ajhal.v6i2.701
Desamsetti, H., & Mandapuram, M. (2017). A Review of Meta-Model Designed for the Model-Based Testing Technique. Engineering International, 5(2), 107–110. https://doi.org/10.18034/ei.v5i2.661 DOI: https://doi.org/10.18034/ei.v5i2.661
Gutlapalli, S. S. (2016a). An Examination of Nanotechnology’s Role as an Integral Part of Electronics. ABC Research Alert, 4(3), 21–27. https://doi.org/10.18034/ra.v4i3.651 DOI: https://doi.org/10.18034/ra.v4i3.651
Gutlapalli, S. S. (2016b). Commercial Applications of Blockchain and Distributed Ledger Technology. Engineering International, 4(2), 89–94. https://doi.org/10.18034/ei.v4i2.653 DOI: https://doi.org/10.18034/ei.v4i2.653
Gutlapalli, S. S. (2017a). Analysis of Multimodal Data Using Deep Learning and Machine Learning. Asian Journal of Humanity, Art and Literature, 4(2), 171–176. https://doi.org/10.18034/ajhal.v4i2.658 DOI: https://doi.org/10.18034/ajhal.v4i2.658
Gutlapalli, S. S. (2017b). The Role of Deep Learning in the Fourth Industrial Revolution: A Digital Transformation Approach. Asian Accounting and Auditing Advancement, 8(1), 52–56. Retrieved from https://4ajournal.com/article/view/77
Gutlapalli, S. S. (2017c). An Early Cautionary Scan of the Security Risks of the Internet of Things. Asian Journal of Applied Science and Engineering, 6, 163–168. Retrieved from https://ajase.net/article/view/14
Gutlapalli, S. S., Mandapuram, M., Reddy, M., & Bodepudi, A. (2019). Evaluation of Hospital Information Systems (HIS) in terms of their Suitability for Tasks. Malaysian Journal of Medical and Biological Research, 6(2), 143–150. https://mjmbr.my/index.php/mjmbr/article/view/661 DOI: https://doi.org/10.18034/mjmbr.v6i2.661
Hosen, M. S., & Gutlapalli, S. S. (2021). A Study of Innovative Class Imbalance Dataset Software Defect Prediction Methods. Asian Journal of Applied Science and Engineering, 10(1), 52–55. https://doi.org/10.18034/ajase.v10i1.52 DOI: https://doi.org/10.18034/ajase.v10i1.52
Hosen, M. S., Thaduri, U. R., Ballamudi, V. K. R., & Lal, K. (2021). Photo-Realistic 3D Models and Animations for Video Games and Films. Engineering International, 9(2), 153–164. https://doi.org/10.18034/ei.v9i2.668 DOI: https://doi.org/10.18034/ei.v9i2.668
Karanjekar, J. B., Chandak, M. B. (2017). Uniform Query Framework for Relational and NoSQL Databases. Computer Modeling in Engineering & Sciences, 113(2), 177-187. https://doi.org/10.3970/cmes.2017.113.177
Kaur, A., Kanwalvir S. D. (2016). Performance Evaluation for Crud Operations in NoSQL Databases. i-manager's Journal on Cloud Computing, 3(2), 1-9. DOI: https://doi.org/10.26634/jcc.3.2.8164
Khan, W., Ahmed, E., Shahzad, W. (2017). Predictive Performance Comparison Analysis of Relational & NoSQL Graph Databases. International Journal of Advanced Computer Science and Applications, 8(5). https://doi.org/10.14569/IJACSA.2017.080564 DOI: https://doi.org/10.14569/IJACSA.2017.080564
Koehler, S., Desamsetti, H., Ballamudi, V. K. R., & Dekkati, S. (2020). Real World Applications of Cloud Computing: Architecture, Reasons for Using, and Challenges. Asia Pacific Journal of Energy and Environment, 7(2), 93-102. https://doi.org/10.18034/apjee.v7i2.698 DOI: https://doi.org/10.18034/apjee.v7i2.698
Lal, K. (2015). How Does Cloud Infrastructure Work?. Asia Pacific Journal of Energy and Environment, 2(2), 61-64. https://doi.org/10.18034/apjee.v2i2.697 DOI: https://doi.org/10.18034/apjee.v2i2.697
Lal, K. (2016). Impact of Multi-Cloud Infrastructure on Business Organizations to Use Cloud Platforms to Fulfill Their Cloud Needs. American Journal of Trade and Policy, 3(3), 121–126. https://doi.org/10.18034/ajtp.v3i3.663 DOI: https://doi.org/10.18034/ajtp.v3i3.663
Lal, K., & Ballamudi, V. K. R. (2017). Unlock Data’s Full Potential with Segment: A Cloud Data Integration Approach. Technology & Management Review, 2(1), 6–12. https://upright.pub/index.php/tmr/article/view/80
Lal, K., Ballamudi, V. K. R., & Thaduri, U. R. (2018). Exploiting the Potential of Artificial Intelligence in Decision Support Systems. ABC Journal of Advanced Research, 7(2), 131-138. https://doi.org/10.18034/abcjar.v7i2.695 DOI: https://doi.org/10.18034/abcjar.v7i2.695
Mandapuram, M. (2017a). Application of Artificial Intelligence in Contemporary Business: An Analysis for Content Management System Optimization. Asian Business Review, 7(3), 117–122. https://doi.org/10.18034/abr.v7i3.650 DOI: https://doi.org/10.18034/abr.v7i3.650
Mandapuram, M. (2017b). Security Risk Analysis of the Internet of Things: An Early Cautionary Scan. ABC Research Alert, 5(3), 49–55. https://doi.org/10.18034/ra.v5i3.650 DOI: https://doi.org/10.18034/ra.v5i3.650
Mandapuram, M., & Hosen, M. F. (2018). The Object-Oriented Database Management System versus the Relational Database Management System: A Comparison. Global Disclosure of Economics and Business, 7(2), 89–96. https://doi.org/10.18034/gdeb.v7i2.657 DOI: https://doi.org/10.18034/gdeb.v7i2.657
Mandapuram, M., Gutlapalli, S. S., Bodepudi, A., & Reddy, M. (2018). Investigating the Prospects of Generative Artificial Intelligence. Asian Journal of Humanity, Art and Literature, 5(2), 167–174. https://doi.org/10.18034/ajhal.v5i2.659 DOI: https://doi.org/10.18034/ajhal.v5i2.659
Mandapuram, M., Gutlapalli, S. S., Reddy, M., Bodepudi, A. (2020). Application of Artificial Intelligence (AI) Technologies to Accelerate Market Segmentation. Global Disclosure of Economics and Business 9(2), 141–150. https://doi.org/10.18034/gdeb.v9i2.662 DOI: https://doi.org/10.18034/gdeb.v9i2.662
Nadeem, Q. M., Culmone, R., Mostarda, L. (2017). Modeling Temporal Aspects of Sensor Data for MongoDB NoSQL Database. Journal of Big Data, 4(1), 1-35. https://doi.org/10.1186/s40537-017-0068-5 DOI: https://doi.org/10.1186/s40537-017-0068-5
Pagán, J. E., Cuadrado, J. S., Molina, J. G. (2015). A Repository for Scalable Model Management. Software and Systems Modeling, 14(1), 219-239. https://doi.org/10.1007/s10270-013-0326-8 DOI: https://doi.org/10.1007/s10270-013-0326-8
Pokorny, J. (2013). NoSQL Databases: A Step to Database Scalability in Web Environment. International Journal of Web Information Systems, 9(1), 69-82. https://doi.org/10.1108/17440081311316398 DOI: https://doi.org/10.1108/17440081311316398
Rats, J. (2017). Use of NoSQL Technology for Secure and Fast Search of Enterprise Data. Baltic Journal of Modern Computing, 5(2), 147-163. https://doi.org/10.22364/bjmc.2017.5.2.01 DOI: https://doi.org/10.22364/bjmc.2017.5.2.01
Reddy, M., Bodepudi, A., Mandapuram, M., & Gutlapalli, S. S. (2020). Face Detection and Recognition Techniques through the Cloud Network: An Exploratory Study. ABC Journal of Advanced Research, 9(2), 103–114. https://doi.org/10.18034/abcjar.v9i2.660 DOI: https://doi.org/10.18034/abcjar.v9i2.660
Seera, N. K., Jain, V. (2015). Perspective of Database Services for Managing Large-Scale Data on the Cloud: A Comparative Study. International Journal of Modern Education and Computer Science, 7(6), 50-58. https://doi.org/10.5815/ijmecs.2015.06.08 DOI: https://doi.org/10.5815/ijmecs.2015.06.08
Thaduri, U. R. (2017). Business Security Threat Overview Using IT and Business Intelligence. Global Disclosure of Economics and Business, 6(2), 123-132. https://doi.org/10.18034/gdeb.v6i2.703 DOI: https://doi.org/10.18034/gdeb.v6i2.703
Thaduri, U. R. (2018). Business Insights of Artificial Intelligence and the Future of Humans. American Journal of Trade and Policy, 5(3), 143–150. https://doi.org/10.18034/ajtp.v5i3.669 DOI: https://doi.org/10.18034/ajtp.v5i3.669
Thaduri, U. R. (2019). Android & iOS Health Apps for Track Physical Activity and Healthcare. Malaysian Journal of Medical and Biological Research, 6(2), 151-156. https://mjmbr.my/index.php/mjmbr/article/view/678
Thaduri, U. R. (2020). Decision Intelligence in Business: A Tool for Quick and Accurate Marketing Analysis. Asian Business Review, 10(3), 193–200. https://doi.org/10.18034/abr.v10i3.670 DOI: https://doi.org/10.18034/abr.v10i3.670
Thaduri, U. R. (2021). Virtual Reality & Artificial Intelligence in Real Estate Business: A Tool for Effective Marketing Campaigns. Asian Journal of Applied Science and Engineering, 10(1), 56–65. https://doi.org/10.18034/ajase.v10i1.54 DOI: https://doi.org/10.18034/ajase.v10i1.54
Thaduri, U. R., & Lal, K. (2020). Making a Dynamic Website: A Simple JavaScript Guide. Technology & Management Review, 5, 15–27. https://upright.pub/index.php/tmr/article/view/81
Thaduri, U. R., Ballamudi, V. K. R., Dekkati, S., & Mandapuram, M. (2016). Making the Cloud Adoption Decisions: Gaining Advantages from Taking an Integrated Approach. International Journal of Reciprocal Symmetry and Theoretical Physics, 3, 11–16. https://upright.pub/index.php/ijrstp/article/view/77
Thodupunori, S. R., & Gutlapalli, S. S. (2018). Overview of LeOra Software: A Statistical Tool for Decision Makers. Technology & Management Review, 3(1), 7–11.
Von D. W. C., Datta, A. (2012). Multiterm Keyword Search in NoSQL Systems. IEEE Internet Computing, 16(1), 34-42. https://doi.org/10.1109/MIC.2011.140 DOI: https://doi.org/10.1109/MIC.2011.140
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