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Journal articles on the topic 'OLBP'

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Published: 5 June 2025

Last updated: 16 July 2025

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Kumar, Ravinder. "Fingerprint Matching Using Rotational Invariant Orientation Local Binary Pattern Descriptor and Machine Learning Techniques." International Journal of Computer Vision and Image Processing 7, no. 4 (2017): 51–67. http://dx.doi.org/10.4018/ijcvip.2017100105.

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The objective of this article is to propose rotation invariant fingerprint descriptor, and a faster and better generalized performance classifier. The author proposes a new multi-resolution analysis based fingerprint descriptor, computed from fingerprint orientation pattern called as orientation local binary pattern (OLBP). The feature vector is constructed by concatenating the OLBP histograms obtained from tessellated ROI of distorted fingerprint images. Secondly, the author proposes a hybrid classifier, which combines a powerful extreme learning machine (ELM) and a well generalized resilient propagation (RPROP). Finally, they propose two hybrid training algorithms using ELM and RPROP. The matching accuracy of 99.9% validates the performance of the proposed OLBP features and the proposed hybrid classification algorithms perform better as compared to the original ELM.

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Anjum, Asma, and Asma Parveen. "Optimized load balancing mechanism in parallel computing for workflow in cloud computing environment." International Journal of Reconfigurable and Embedded Systems (IJRES) 12, no. 2 (2023): 276. http://dx.doi.org/10.11591/ijres.v12.i2.pp276-286.

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Cloud computing gives on-demand access to computing resources in metered and powerfully adapted way; it empowers the client to get access to fast and flexible resources through virtualization and widely adaptable for various applications. Further, to provide assurance of productive computation, scheduling of task is very much important in cloud infrastructure environment. Moreover, the main aim of task execution phenomena is to reduce the execution time and reserve infrastructure; further, considering huge application, workflow scheduling has drawn fine attention in business as well as scientific area. Hence, in this research work, we design and develop an optimized load balancing in parallel computation aka optimal load balancing in parallel computing (OLBP) mechanism to distribute the load; at first different parameter in workload is computed and then loads are distributed. Further OLBP mechanism considers makespan time and energy as constraint and further task offloading is done considering the server speed. This phenomenon provides the balancing of workflow; further OLBP mechanism is evaluated using cyber shake workflow dataset and outperforms the existing workflow mechanism.

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Asma, Anjum, and Parveen Asma. "Optimized load balancing mechanism in parallel computing for workflow in cloud computing environment." International Journal of Reconfigurable and Embedded Systems (IJRES) 12, no. 2 (2023): 276–86. https://doi.org/10.11591/ijres.v12.i2.pp276-286.

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Ma, Yingdong, Liang Deng, Xiankai Chen, and Ning Guo. "Integrating Orientation Cue With EOH-OLBP-Based Multilevel Features for Human Detection." IEEE Transactions on Circuits and Systems for Video Technology 23, no. 10 (2013): 1755–66. http://dx.doi.org/10.1109/tcsvt.2013.2268991.

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Buchanan, Taylor, Deanna Rumble, Kristen Allen-Watts, et al. "Associations of pain severity and mobility with age in chronic low back pain: does the type of assessment matter?" Innovation in Aging 5, Supplement_1 (2021): 886. http://dx.doi.org/10.1093/geroni/igab046.3224.

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Abstract Chronic low back pain (cLBP) can lead to severe pain symptoms as well as disability in adults. As individuals age, pain symptoms and mobility outcomes can become increasingly debilitating. However, current findings regarding the influence of age on symptoms and outcomes are mixed and may be attributed to the assessment methodologies for pain and mobility. Therefore, we sought to examine the association of age with broad and specific assessments of pain severity and mobility commonly implemented in adults with cLBP. cLBP participants (n = 158) completed questionnaires regarding pain intensity and disability including demographics, Clinical Pain Assessment (CPA) and the Oswestry Low Back Pain questionnaire (OLBP). Participants also completed assessments of movement-evoked pain and difficulty by performing the Short Physical Performance Battery (SPPB). Pearson’s chi-square tests and regression-based analyses were conducted using SPSS version 26.0. Among cLBP participants, age was associated with pain-related disability indexed by section one of the OLBPS regarding pain intensity (F= 5.0, p&lt;.05), and mobility via total SPPB score (F= 11.7, p&lt;.05). Interestingly, age predicted greater self-reported difficulty climbing stairs (F= 21.7, p&lt;.05), performing chores (F= 17.0, p&lt;.05), walking (F= 14.0, p&lt;.05), and running errands (F= 13.4, p&lt;.05) from the CPA. Further, age predicted total balance (F= 3.2, p&lt;.05), gait speed (F= 7.8, p&lt;.05), and chair stand (F= 6.5, p&lt;.05) scores of SPPB. Age is associated with questionnaires assessing cLBP pain severity and is also associated with mobility outcomes. Future research should seek to understand the influence of age on movement-evoked pain in cLBP.

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Vatresia, Arie, Asahar Johar, Ferzha Putra Utama, and Sinta Iryani. "Automated Data Integration of Biodiversity with OLAP and OLTP." SISFORMA 7, no. 2 (2020): 80. http://dx.doi.org/10.24167/sisforma.v7i2.2817.

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Biodiversity is one of emerging issue over decades; many have performed research to map and to document the data over the world. This issue is very important due to the event of extinction have been accelerating happening because of human extinction. Bengkulu, as one of the province lied in one of 19 hotspots in the world, Sundanese, has experienced the degradation of flora and fauna over the case of forest degradation and habitat loss. Although many application and software has been developed to solve the case, the existences of data standardization still become an issue over this problem. In this research, study of data integration had been developed to make the process of biodiversity data acquisition can be more effective and efficient. The system proposed the integration based on OLAP and OLTP that will be connected to IUCN, as one of the biggest center for monitoring the loss of biodiversity all around the world. This application had been built with web based using UML design and followed SDLC to provide the best fit of the need. This research had also succeeded to build the automated integration to show the record of dynamic number over biodiversity existences in Bengkulu. The application had been tested using black box and has the perfect performance (100%) over the testing that can help the monitoring process over biodiversity data.

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Funke, Florian, Alfons Kemper, and Thomas Neumann. "Compacting transactional data in hybrid OLTP&OLAP databases." Proceedings of the VLDB Endowment 5, no. 11 (2012): 1424–35. http://dx.doi.org/10.14778/2350229.2350258.

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Rachapudi, Sandeep. "Holistic Data Management: Integrating OLTP and OLAP in Financial Systems." International Journal of Science and Research (IJSR) 13, no. 10 (2024): 1115–18. http://dx.doi.org/10.21275/sr241015110206.

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Jankauskas, Robertas, and Dmitrij Šešok. "Duomenų migravimo iš OLTP į OLAP duomenų bazę greitaveikos tyrimas." Jaunųjų mokslininkų darbai 47, no. 2 (2017): 42–49. http://dx.doi.org/10.21277/jmd.v47i2.136.

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Duomenų sinchronizacija tarp kelių sistemų yra vienas iš dažniausiai pasitaikančių procesų. Iš esamų duomenų norima atlikti analizę, kuria naudojantis būtų galima priimti tam tikrus sprendimus, padėsiančius pateikti išvadas apie organizacijų veiklas. Šiame darbe analizuojamas duomenų migravimo procesas tarp „Oracle“ ir „Microsoft SQL Server“ duomenų bazių valdymo sistemų naudojantis skirtingomis duomenų įkėlimo metodologijomis ir sistemų teikiamomis technologijomis.

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Lenz, Hans-J., and Bernhard Thalheim. "A Formal Framework of Aggregation for the OLAP-OLTP Model." JUCS - Journal of Universal Computer Science 15, no. (1) (2009): 273–303. https://doi.org/10.3217/jucs-015-01-0273.

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OLAP applications are widely used in business applications. They are often (implicitly) defined on top of OLTP systems and extensively use aggregation and transformation functions. The main OLAP data structure is a multidimensional table with three kinds of attributes: so-called dimension attributes, implicit attributes given by aggregation functions and fact attributes. Domains of dimension attributes are structured and thus support a variety of aggregations. These aggregations are used to generate new values for the fact attributes. In this paper we systematically develop a theory for OLAP applications. We first define aggregation functions and use these to introduce an OLAP algebra. Based on these foundations we derive properties that guarantee or contradict correctness of OLAP computations. Finally, for pragmaticatreatment of OLAP applications the OLTP-OLAP specification frame is introduced.

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Camilleri, Carl, Joseph G. Vella, and Vitezslav Nezval. "HTAP With Reactive Streaming ETL." Journal of Cases on Information Technology 23, no. 4 (2021): 1–19. http://dx.doi.org/10.4018/jcit.20211001.oa10.

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In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empirically show that, under an OLTP workload, a row-store DBMS sustains a 1000 times higher throughput than a columnar DBMS, whilst OLAP queries are more than 4 times faster on a columnar DBMS. Finally, a reactive streaming ETL pipeline is implemented which connects these two DBMSs. Separate benchmarks show that OLTP events can be streamed to an OLAP database within a few seconds.

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Chaalal, Hichem, Nicolas Travers, and Hafida Belbachir. "T-plotter: A new data structure to reconcile OLAP and OLTP models." Multiagent and Grid Systems 15, no. 3 (2019): 237–57. http://dx.doi.org/10.3233/mgs-190311.

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Salaki, R. J., J. Waworuntu, and I. R. H. T. Tangkawarow. "Extract transformation loading from OLTP to OLAP data using pentaho data integration." IOP Conference Series: Materials Science and Engineering 128 (April 2016): 012020. http://dx.doi.org/10.1088/1757-899x/128/1/012020.

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SanthoshBaboo, S., and P. Renjith Kumar. "Next Generation Data Warehouse Design with OLTP and OLAP Systems Sharing same Database." International Journal of Computer Applications 72, no. 13 (2013): 45–50. http://dx.doi.org/10.5120/12557-9282.

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Honda, Masayuki, and Takehiro Matsumoto. "System Replacement to a New HIS and Data Warehouse." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 1 (2012): 38–41. http://dx.doi.org/10.20965/jaciii.2012.p0038.

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Large-scale hospital information systems (HIS) generally consist of (i) online transaction processing (OLTP) and (ii) online analytical processing (OLAP) systems. Electronic medical records (EMR) are a major OLTP element. The data warehouse (DWH) assumes many important OLAP roles and maintains an institution’s medical care at a high level by providing EMR with the best practice cases available. This article focuses mainly on why OLTP and OLAP are needed and what roles the DWH plays, which means that the DWH has its own utilities and supplementary merits. The background of this discussion is closely related to the HIS at Nagasaki University Hospital introduced before the DWH is discussed.

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Lee, Juchang, SeungHyun Moon, Kyu Hwan Kim, Deok Hoe Kim, Sang Kyun Cha, and Wook-Shin Han. "Parallel replication across formats in SAP HANA for scaling out mixed OLTP/OLAP workloads." Proceedings of the VLDB Endowment 10, no. 12 (2017): 1598–609. http://dx.doi.org/10.14778/3137765.3137767.

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Jing, Changhong, Wenjie Liu, Jintao Gao, and Ouya Pei. "Research and implementation of HTAP for distributed database." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 2 (2021): 430–38. http://dx.doi.org/10.1051/jnwpu/20213920430.

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Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterprises continues to increase, distributed databases have gradually replaced stand-alone databases and become the mainstream of applications. However, the current business supported by distributed databases is mainly based on OLTP applications, lacking OLAP implementation. This paper proposes an implementation method of HTAP for distributed database CBase, which provides an implementation method of OLAP analysis for CBase, and can easily deal with data analysis of large amounts of data.

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Opoku-Anokye, Stephen, and Yinshan Tang. "Design of a Unified Data with Business Rules Storage Model for OLTP and OLAP Systems." Journal of Computing and Information Technology 22, LISS 2013 (2014): 63. http://dx.doi.org/10.2498/cit.1002263.

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Lee, Juchang, Wook-Shin Han, Hyoung Jun Na, et al. "Parallel replication across formats for scaling out mixed OLTP/OLAP workloads in main-memory databases." VLDB Journal 27, no. 3 (2018): 421–44. http://dx.doi.org/10.1007/s00778-018-0503-z.

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Shobirin, Kheri Arionadi, Adi Panca Saputra Iskandar, and Ida Bagus Alit Swamardika. "Data Warehouse Schemas using Multidimensional Data Model for Retail." International Journal of Engineering and Emerging Technology 2, no. 1 (2017): 84. http://dx.doi.org/10.24843/ijeet.2017.v02.i01.p17.

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A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.

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Zhang, Chao, Guoliang Li, and Tao Lv. "HyBench: A New Benchmark for HTAP Databases." Proceedings of the VLDB Endowment 17, no. 5 (2024): 939–51. http://dx.doi.org/10.14778/3641204.3641206.

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In this paper, we propose, HyBench, a new benchmark for HTAP databases. First, we generate the testing data by simulating a representative HTAP application. We particularly develop a time-dependent generation phase and an anomaly generation phase for testing HTAP with large cardinality and various anomalies. Second, we propose a set of hybrid workloads. Specifically, we design 18 read/write transactions, 13 analytical queries, and a mix workload of 6 analytical transactions and 6 interactive queries. We also develop a graph-based parameter curation method to control the access patterns including skew access and data contention of the hybrid workload. Third, we propose a unified metric for quantifying the overall HTAP performance. Particularly, we introduce a query-driven method that evaluates the data freshness (lag time between analytics and transactions). Then we introduce a three-phase execution rule to compute a unified metric, combining the performance of OLTP (TPS), OLAP (QPS), and OLXP (XPS) and data freshness. To verify the effectiveness of HyBench and to debunk the myth of different HTAP architectures, extensive experiments have been conducted over five HTAP databases.

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Kelly, Richard J., Nicola Houghton, Talha Munir, et al. "52-Week Open-Label Extension Data from a Phase 2 Study Evaluating the Safety and Efficacy of Pozelimab and Cemdisiran Combination Therapy in Patients with Paroxysmal Nocturnal Hemoglobinuria Who Switched from Eculizumab." Blood 142, Supplement 1 (2023): 2716. http://dx.doi.org/10.1182/blood-2023-188671.

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Background: Paroxysmal nocturnal hemoglobinuria (PNH) is an ultra-rare, acquired disorder, leading to impaired expression of complement-regulating proteins on the surface of hematopoietic cells. Complement component C5 inhibitors are part of the standard of care for patients with PNH; however, these are generally intravenous treatments. Pozelimab and cemdisiran are investigational agents with a small volume subcutaneous (SC) once every 4 weeks maintenance regimen that may be self-administered. Both inhibit terminal complement through complementary mechanisms of action. Cemdisiran is an N-acetylgalactosamine-conjugated small interfering RNA that suppresses liver production of C5, while pozelimab is a fully human monoclonal antibody inhibitor of C5. The efficacy and safety of the combination of pozelimab and cemdisiran was evaluated in an open-label, single-arm study in patients with PNH who switched from eculizumab therapy (NCT04888507). The completed safety and efficacy data of the optional 52-week open-label extension period (OLEP) are presented. Methods: Patients who completed the 32-week open-label treatment period (OLTP) were offered to participate in an optional 52-week OLEP. Patients were adults with PNH who had switched from stable eculizumab therapy to the combination (pozelimab 400 mg and cemdisiran 200 mg) SC every 4 weeks in the OLTP. The study enrolled two patients who were previously treated with higher doses of eculizumab (1200 mg or 1500 mg every two weeks). The results of the 32-week OLTP have been previously presented; the results of the subsequent 52-week OLEP are presented here. Results: All five patients who completed the OLTP were enrolled in and completed the OLEP. After completing the OLEP, all patients transitioned to an expanded access program to continue the combination of pozelimab and cemdisiran. At baseline of the OLTP, lactate dehydrogenase (LDH) was well controlled on eculizumab and remained controlled during the 32-week OLTP. During the 52-week OLEP, no patient had an LDH greater than 1.5 x the upper limit of normal (ULN; Figure) at any of the scheduled study visits or met the protocol criteria for breakthrough hemolysis (either by central or local laboratory values; defined as an increase in LDH [LDH ≥2 x ULN if pre-treatment LDH ≤1.5 x ULN, or LDH ≥2 x ULN subsequent to initial achievement of LDH ≤1.5 x ULN if pre-treatment LDH &gt;1.5 x ULN] with concomitant signs or symptoms associated with hemolysis). The two patients who previously received higher doses of eculizumab also maintained control of LDH levels throughout the OLTP and OLEP. Four of five patients remained transfusion free, but one patient required a blood transfusion while hospitalized with an acute complement-activating condition. This patient experienced two serious and severe treatment-emergent adverse events of respiratory infection and consequently acute hemolysis that did not meet the trial criteria for breakthrough hemolysis but was reported as an adverse event based on clinical judgement. The investigator and sponsor assessed these events as not treatment related. CH50, a measure of terminal complement activity at fixed time points, remained suppressed throughout the study in all patients. No other serious or severe adverse events were reported. There were no meningococcal infections, thrombotic events, or TEAEs leading to death. Conclusions: Results suggest that, in patients with PNH transitioning from eculizumab treatment, the combination of pozelimab and cemdisiran was generally well tolerated and provided long term sustained control of intravascular hemolysis without any breakthrough hemolysis events. Findings support the ongoing development of pozelimab and cemdisiran combination therapy.

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Rose, Banaybanay, Bulalaque Claire, Dela Cruz Krishan Aea C, et al. "Understanding the Role of OLAP and OLTP in Managing and Interpreting Student Data for SEAIT Scholarship System." International Journal of Scientific and Academic Research 04, no. 09 (2024): 17–28. https://doi.org/10.54756/ijsar.2024.18.

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This study understandsthe role of OLAP and OLTP in Managing and Interpreting Student Data for SEAIT Scholarship System. Using qualitative methods, such as semi-structured interviews and focus group discussions, the research investigates the experiences and perspectives of key stakeholders, including scholarship coordinatorand administrative staffs.The findings reveal challenges in the current system, such as inefficiencies in data retrieval, delays in reporting, and difficulties in real-time data access. Stakeholders highlighted the need for improved data analytics and transactional processing to support better decision-making and operational efficiency. The study identifies key areas for enhancement, including the integration of OLAP for advanced reporting and insights and OLTP for real-time transactional support.By providing a qualitative analysis of the stakeholders' experiences and expectations, this research offers valuable recommendations for improving the SEAIT Scholarship System. These include implementing a more robust data management framework, training staff on analytical tools, and ensuring system scalability to meet future demands

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Liu, Bin, Zhengyu Yang, Jiaqing Wu, and Jie Gu. "OLAP analysis of user energy consumption based on multitemporal distribution characteristics." Journal of Physics: Conference Series 2290, no. 1 (2022): 012045. http://dx.doi.org/10.1088/1742-6596/2290/1/012045.

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Abstract With the development of databases, online transaction processing (OLTP) can no longer meet the needs of end users for database query and analysis, and the simple query of large databases by SQL can not meet the requirements of end user analysis. Therefore, online analytical processing (OLAP) is proposed. concept. On the one hand, we explained the basic knowledge of OLAP, including OLAP multidimensional data concept, multidimensional data structure, multidimensional data analysis, characteristics, etc. On the other hand, we established an OLAP analysis model of the multi-temporal and spatial distribution characteristics of user energy consumption, which is refined provide support for the analysis of user energy consumption behavior.

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Kovač, Marta, Michał Gorczak, Marta Wrzosek, Cezary Tkaczuk, and Milan Pernek. "Identification of Entomopathogenic Fungi as Naturally Occurring Enemies of the Invasive Oak Lace Bug, Corythucha arcuata (Say) (Hemiptera: Tingidae)." Insects 11, no. 10 (2020): 679. http://dx.doi.org/10.3390/insects11100679.

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The oak lace bug (OLB), Corythucha arcuata (Hemiptera: Tingidae), was first identified as an invasive pest in Europe in northern Italy in 2000 and since then it has spread rapidly, attacking large forested areas in European countries. The OLB is a cell sap-sucking insect that is native to North America, with Quercus spp. as its main host. Its rapid expansion, successful establishment in invaded countries, and observations of more damage to hosts compared to native areas are most likely due to a lack of natural enemies, pathogens and competitors. In its native area, various natural enemies of OLBs have been identified; however, little is known about the occurrence and impact of OLB pathogens. None of the pathogenic fungi found on OLBs in natural conditions have been identified until now. In this study, we provide evidence of four entomopathogenic fungi that are naturally occurring on invasive OLBs found in infested pedunculate oak forests in eastern Croatia. On the basis of their morphology and multilocus molecular phylogeny, the fungi were identified as Beauveria pseudobassiana, Lecanicillium pissodis, Akanthomyces attenuatus and Samsoniella alboaurantium. The sequences generated for this study are available from GenBank under the accession numbers MT004817-MT004820, MT004833-MT004835, MT027501-MT27510, and MT001936-MT0011943. These pathogenic species could facilitate biological control strategies against OLBs.

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Wang, Jianying, Tongliang Li, Haoze Song, et al. "PolarDB-IMCI: A Cloud-Native HTAP Database System at Alibaba." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–25. http://dx.doi.org/10.1145/3589785.

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Cloud-native databases have become the de-facto choice for mission-critical applications on the cloud due to the need for high availability, resource elasticity, and cost efficiency. Meanwhile, driven by the increasing connectivity between data generation and analysis, users prefer a single database to efficiently process both OLTP and OLAP workloads, which enhances data freshness and reduces the complexity of data synchronization and the overall business cost. In this paper, we summarize five crucial design goals for a cloud-native HTAP database based on our experience and customers' feedback, i.e., transparency, competitive OLAP performance, minimal perturbation on OLTP workloads, high data freshness, and excellent resource elasticity. As our solution to realize these goals, we present PolarDB-IMCI, a cloud-native HTAP database system designed and deployed at Alibaba Cloud. Our evaluation results show that PolarDB-IMCI is able to handle HTAP efficiently on both experimental and production workloads; notably, it speeds up analytical queries up to ×149 on TPC-H (100GB). PolarDB-IMCI introduces low visibility delay and little performance perturbation on OLTP workloads (<5%), and resource elasticity can be achieved by scaling out in tens of seconds.

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Tong, Bing, Yan Zhou, Chen Zhang, et al. "Galaxybase: A High Performance Native Distributed Graph Database for HTAP." Proceedings of the VLDB Endowment 17, no. 12 (2024): 3893–905. http://dx.doi.org/10.14778/3685800.3685814.

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We introduce Galaxybase, a native distributed graph database that addresses the increasing demands for processing large volumes of graph data in diverse industries like finance, manufacturing, and government. Designed to handle the requirements of both transactional and analytical workloads, Galaxybase stands out with its novel data storage and transaction mechanisms. At its core, Galaxybase utilizes a Log-Structured Adjacency List coupled with an Edge Page structure, optimizing read-write operations across a spectrum of tasks such as graph traversals and single edge queries. A notable aspect of Galaxybase is its execution of custom distributed transaction modes tailored for HTAP transactions, allowing for the facilitation of bidirectional and interactive transactions. It ensures data integrity and minimal latency while enabling simultaneous processing of OLTP and OLAP workloads without blocking. Experimental results show that Galaxybase achieves high throughput and low latency in both OLTP and OLAP workloads, across various graph query scenarios and resource conditions. Galaxybase has been deployed in leading banks, education, telecommunication and energy sectors in China, consistently maintaining robust performance for HTAP workloads over the years.

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Сайлау қызы, Жұлдыз, Амерханов Амерханов, Бакытжан Шодырова та Асем Аубакирова. "СОВРЕМЕННЫЕ АРХИТЕКТУРНЫЕ ПОДХОДЫ К ОБРАБОТКЕ ГИБРИДНЫХ АНАЛИТИЧЕСКИХ ЗАПРОСОВ В HPC-СИСТЕМАХ". Вестник Алматинского университета энергетики и связи 2, № 69 (2025): 170–81. https://doi.org/10.51775/2790-0886_2025_69_2_170.

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Статья посвящена исследованию современных подходов к обработке гибридных аналитических запросов в высокопроизводительных вычислительных системах (НРС), совмещающих транзакционные (OLTP) и аналитические (OLAP) нагрузки. Основное внимание уделено архитектурам гибридных систем управления базами данных (СУБД), обеспечивающим эффективную интеграцию OLTP- и OLAP-компонентов в рамках единого вычислительного окружения. В качестве примеров рассматриваются системы HADAD и Greenplum, демонстрирующие высокую эффективность за счёт реализации механизмов балансировки нагрузки, масштабируемости и интеллектуальной оптимизации выполнения запросов при работе с большими объёмами данных. В рамках экспериментального исследования проведено сравнительное тестирование реляционных СУБД (SQL Server, PostgreSQL) и нереляционных решений (MongoDB, GraphQL). Установлено, что реляционные СУБД обеспечивают высокую производительность благодаря использованию параллельной обработки запросов и продвинутых методов индексирования. В то же время нереляционные СУБД проявляют конкурентные преимущества в специализированных задачах, связанных с обработкой неструктурированных данных и анализом графовых структур. Полученные результаты подчеркивают необходимость выбора архитектурно и технологически обоснованных решений в зависимости от характера нагрузки, структуры обрабатываемых данных и требований к аналитическим операциям. Представленные выводы могут быть использованы при проектировании и оптимизации информационных систем, ориентированных на работу с гибридными запросами в условиях больших данных.

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Yoon, Seung-Chul, Tae Sung Shin, Kurt Lawrence, and Deana R. Jones. "Development of Online Egg Grading Information Management System with Data Warehouse Technique." Applied Engineering in Agriculture 36, no. 4 (2020): 589–604. http://dx.doi.org/10.13031/aea.13675.

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Highlights Digital data collection and management system is developed for the USDA-AMS’s shell-egg grading program. Database system consisting of OLTP, data warehouse and OLAP databases enables online data entry and trend reporting. Data and information management is done through web application servers. Users access the databases via web browsers. Abstract . This paper is concerned with development of web-based online data entry and reporting system, capable of centralized data storage and analytics of egg grading records produced by USDA egg graders. The USDA egg grading records are currently managed in paper form. While there is useful information for data-driven knowledge discovery and decision making, the paper-based egg grading record system has fundamental limitations in effective and timely management of such information. Thus, there has been a demand to electronically and digitally store and manage the egg grading records in a database for data analytics and mining, such that the quality trends of eggs observed at various levels (e.g., nation or state) are readily available to decision makers. In this study, we report the design and implementation of a web-based online data entry and reporting information system (called USDA Egg Grading Information Management System, EGIMS), based on a data warehouse framework. The developed information system consisted of web applications for data entry and reporting, and internal databases for data storage, aggregation, and query processing. The internal databases consisted of online transaction processing (OLTP) database for data entry and retrieval, data warehouse (DW) for centralized data storage and online analytical processing (OLAP) database for multidimensional analytical queries. Thus, the key design goal of the system was to build a system platform that could provide the web-based data entry and reporting capabilities while rapidly updating the OLTP, DW and OLAP databases. The developed system was evaluated by a simulation study with statistically-modeled egg grading records of one hypothetical year. The study found that the EGIMS could handle approximately up to 600 concurrent users, 32 data entries per second and 164 report requests per second, on average. The study demonstrated the feasibility of an enterprise-level data warehouse system for the USDA and a potential to provide data analytics and data mining capabilities such that the queries about historical and current trends can be reported. Once fully implemented and tested in the field, the EGIMS is expected to provide a solution to modernize the egg grading practice of the USDA and produce the useful information for timely decisions and new knowledge discovery. Keywords: Data warehouse, Database, OLTP, OLAP, Egg grading, Information management, Web application, Information system, Data.

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AGRAFIOTIS, ATHANASIOS. "Cloud Computing: Testing a Key Generation Encryption Algorithm." International Journal of Computer Science and Mobile Computing 13, no. 6 (2024): 59–67. http://dx.doi.org/10.47760/ijcsmc.2024.v13i06.008.

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On the cloud computing the number of instances represents the space that application shares. AI artificial intelligence and machine learning nowadays has been used as a provision system for virtualization purposes in the cloud. A database on cloud is hosted in an instance and is ready to be filled with data. Database is an organized collection of information that is stored and accessed by applications. Database instance contains raw data, figures, values. Database Management System it is possible to manage data such as queries and table schema. An example of database management system where all the utilities that the system offers, dbms is the interface system of the database, that includes data storage, data retrieval administration, reports and data security. The database makes use of a schema which is a set of rules. The table that is part of the database can be organized as a schema. The importance of the database is to ensure that data are stored and later to be accessed. Technologies are using schema, write into the database entries into separate tables. Operational data is the data produced by the organizations. Transaction are the operations that take place into the database such as updates. Next the OLTP represents the online transaction processing. Applications that makes use of queries are ATM (automated teller machine). The OLTP is make use of the ACID model(atomic,changing,isolation, durables) are transactions that takes place under specific constraints. Modern technologies are facing issues such as high volume data on the database and low-latency of the OLTP system. OLAP is the data analysis, and are technologies of data aggregation and queuing them using ascending ordering. The technologies are highly depend to each other the OLTP applications that handles operational data and the OLAP that querying them for aggregation analysis. Scaling the process of managing the underlying resources. The scale up handles the computing power and the temporary memory that is required for an instance to run and the scale out increase the number of databases. Data warehouse is a single place data from multiple data sources. Ingest large amounts of data, optimized for OLAP use cases. In a data warehouse makes uses of big data and are petabytes. Row is going to be transformed to a new structure OLTP database. Data Lake is a centralized repository for storing all structured and unstructured data. Keeps the collected data and is not possible to transformed the data or copy them.

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Difallah, Djellel Eddine, Andrew Pavlo, Carlo Curino, and Philippe Cudre-Mauroux. "OLTP-Bench." Proceedings of the VLDB Endowment 7, no. 4 (2013): 277–88. http://dx.doi.org/10.14778/2732240.2732246.

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Kadić, Simonida. "ARHITEKTURA I IMPLEMENTACIJA SISTEMA ZA ANALIZU PODATAKA PAMETNOG GRADA." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 34, no. 09 (2019): 1519–22. http://dx.doi.org/10.24867/04be03kadic.

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U ovom radu prezentovan je sistem skladišta podataka čijom je upotrebom moguće vršiti analize kretanja ljudi na području grada Melburna u Australiji. U prvom delu rada opisani su izvori podataka. Podaci su prikupljeni iz baza podataka vladinih agencija grada Melburna. Dobavljanje podataka zahtevalo je razvoj podsistema za ekstrakciju podataka. Neophodno je bilo izvršiti eksplorativnu analizu prikupljenih podataka, kako bi se razvila OLTP šema baze podataka i programi za punjenje njenih tabela. Za projektovanje dimenzija i činjenica OLAP šeme baze podataka bilo je potrebno uočiti poslovne procese koji su od značaja za analizu kretanja ljudi. Takođe, razvijen je ETL proces čijom primenom se realizuje punjenje OLAP baze podataka. Izveštajna funkcija omogućava parametrizaciju upita.

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Admin, Admin. "A Extract, Transform, Load sebagai upaya Pembangunan Data Warehouse." Journal of Informatics and Communication Technology (JICT) 1, no. 1 (2019): 11–20. http://dx.doi.org/10.52661/j_ict.v1i1.11.

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Paper ini dibuat untuk memberikan gambaran secara general dalam proses transformasi Ekstract, Transform, dan Load (ETL) sebagai data masukan untuk multidimensional modeling data mart dan data warehouse. Artikel ini dibuat dengan mengimplementasikan database dari Online Transaction Processing (OLTP) kedalam database Online Analytical processing (OLAP). Pada penelitian ini digunakan database classicmodels yang bersifat open source dari Mysql.Metode yang dilakukan dalam penelitian ini adalah, dengan melakukan proses Extract, Transform danLoad (ETL) pada data classic models yang dilakukan dengan cara melakukan ketiga proses tersebut (ETL) dari database OLTP kedalam database OLAP.Luaran dari penelitian ini adalah terbntuknya fact oder berisi data dari semua data dimension yang dbiuat untuk data classic model menggunakan perngkat lunak Pentaho Data Intergarion (Kettle) dan database management system MySQL

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Iskandar, Ade Rahmat, Apri Junaidi, and Asep Herman. "Extract, Transform, Load sebagai upaya Pembangunan Data Warehouse." Journal of Informatics and Communication Technology (JICT) 1, no. 1 (2019): 25–35. http://dx.doi.org/10.52661/j_ict.v1i1.21.

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Rehrmann, Robin, Carsten Binnig, Alexander Böhm, Kihong Kim, and Wolfgang Lehner. "Sharing opportunities for OLTP workloads in different isolation levels." Proceedings of the VLDB Endowment 13, no. 10 (2020): 1696–708. http://dx.doi.org/10.14778/3401960.3401967.

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OLTP applications are usually executed by a high number of clients in parallel and are typically faced with high throughput demand as well as a constraint latency requirement for individual statements. Interestingly, OLTP workloads are often read-heavy and comprise similar query patterns, which provides a potential to share work of statements belonging to different transactions. Consequently, OLAP techniques for sharing work have started to be applied also to OLTP workloads, lately. In this paper, we present an approach for merging read statements within interactively submitted multi-statement transactions consisting of reads and writes. We first define a formal framework for merging transactions running under a given isolation level and provide insights into a prototypical implementation of merging within a commercial database system. In our experimental evaluation, we show that, depending on the isolation level, the load in the system and the read-share of the workload, an improvement of the transaction throughput by up to a factor of 2.5X is possible without compromising the transactional semantics.

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Chen, Jianjun, Yonghua Ding, Ye Liu, et al. "ByteHTAP." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3411–24. http://dx.doi.org/10.14778/3554821.3554832.

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In recent years, at ByteDance, we see more and more business scenarios that require performing complex analysis over freshly imported data, together with transaction support and strong data consistency. In this paper, we describe our journey of building ByteHTAP, an HTAP system with high data freshness and strong data consistency. It adopts a separate-engine and shared-storage architecture. Its modular system design fully utilizes an existing ByteDance's OLTP system and an open source OLAP system. This choice saves us a lot of resources and development time and allows easy future extensions such as replacing the query processing engine with other alternatives. ByteHTAP can provide high data freshness with less than one second delay, which enables many new business opportunities for our customers. Customers can also configure different data freshness thresholds based on their business needs. ByteHTAP also provides strong data consistency through global timestamps across its OLTP and OLAP system, which greatly relieves application developers from handling complex data consistency issues by themselves. In addition, we introduce some important performance optimizations to ByteHTAP, such as pushing computations to the storage layer and using delete bitmaps to efficiently handle deletes. Lastly, we will share our lessons and best practices in developing and running ByteHTAP in production.

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Song, Haoze, Wenchao Zhou, Feifei Li, Xiang Peng, and Heming Cui. "Rethink Query Optimization in HTAP Databases." Proceedings of the ACM on Management of Data 1, no. 4 (2023): 1–27. http://dx.doi.org/10.1145/3626750.

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The advent of data-intensive applications has fueled the evolution of hybrid transactional and analytical processing (HTAP). To support mixed workloads, distributed HTAP databases typically maintain two data copies that are specially tailored for data freshness and performance isolation. In particular, a copy in a row-oriented format is well-suited for OLTP workloads, and a second copy in a column-oriented format is optimized for OLAP workloads. Such a hybrid design opens up a new design space for query optimization: plans can be optimized over different data formats and can be executed over isolated resources, which we term hybrid plans. In this paper, we demonstrate that hybrid plans can largely benefit query execution (e.g., up to 11x speedups in our evaluation). However, we also found these benefits will potentially be at the cost of sacrificing data freshness or performance isolation since traditional optimizers may not precisely model and schedule the execution of hybrid plans on real-time updated HTAP databases. Therefore, we propose Metis, an HTAP-aware optimizer. We show, both theoretically and experimentally, that using the proposed optimizations, a system can largely benefit from hybrid plans while preserving isolated performance for OLTP and OLAP, and these optimizations are robust to the changes in workloads.

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Tyrychtr, Jan, Martin Pelikán, Hana Štiková, and Ivan Vrana. "EM-OLAP Framework." Business & Information Systems Engineering 60, no. 6 (2018): 543–62. http://dx.doi.org/10.1007/s12599-018-0533-5.

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Walid, Qassim Qwaider. "Apply On-Line Analytical Processing (OLAP)With Data Mining For Clinical Decision Support." International Journal of Managing Information Technology (IJMIT) 4, no. 1 (2012): 1 to 13. https://doi.org/10.5281/zenodo.3667051.

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Medicine is a new direction in his mission is to prevent, diagnose and medicate diseases using OLAP with data mining. Are analyzed clinical data on patient population and the wide range of performance management of health care, unfortunately, are not converted to useful information for effective decision making. Built OLAP and data mining techniques in the field of health care, and an easy to use decision support platform, which supports the decision-making process of caregivers and clinical managers. This paper presents a model for clinical decision support system which combines the strengths of both OLAP and data mining. It provides a knowledge rich environment that cannot be achieved by using OLAP or data mining alone.  

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Nirwansyah, Ferdy, and Suharjito Suharjito. "Hybrid Disk Drive Configuration on Database Server Virtualization." Indonesian Journal of Electrical Engineering and Computer Science 2, no. 3 (2016): 720. http://dx.doi.org/10.11591/ijeecs.v2.i3.pp720-728.

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SSD is a revolutionary new storage technologies. Enterprise storage system using full SSD is still very expensive, while HDD is still widely used. This study discusses hybrid configuration storage in virtualized server database with benchmark against four hybrid storage configuration for four databases, ORACLE, SQL Server, MySQL and PostgreSQL on Windows Server virtualization. Benchmark using TPC-C and TPC-H to get the best performance of four configurations were tested. The results of this study indicate HDD storage configurations as visual disk drive OS and SSD as visual disk drives database get better performance as OLTP and OLAP database server compared with SSD as visual disk drive OS and HDD as a visual disk drive database. Based on the data research TPC-C, OLTP get best performance at HDD storage configurations as visual disk drive OS and SSD as a visual disk drives database and temporary files.

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Lesur, Olivier, Frédéric Chagnon, Réjean Lebel, and Martin Lepage. "In Vivo Endomicroscopy of Lung Injury and Repair in ARDS: Potential Added Value to Current Imaging." Journal of Clinical Medicine 8, no. 8 (2019): 1197. http://dx.doi.org/10.3390/jcm8081197.

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Background: Standard clinical imaging of the acute respiratory distress syndrome (ARDS) lung lacks resolution and offers limited possibilities in the exploration of the structure–function relationship, and therefore cannot provide an early and clear discrimination of patients with unexpected diagnosis and unrepair profile. The current gold standard is open lung biopsy (OLB). However, despite being able to reveal precise information about the tissue collected, OLB cannot provide real-time information on treatment response and is accompanied with a complication risk rate up to 25%, making longitudinal monitoring a dangerous endeavor. Intravital probe-based confocal laser endomicroscopy (pCLE) is a developing and innovative high-resolution imaging technology. pCLE offers the possibility to leverage multiple and specific imaging probes to enable multiplex screening of several proteases and pathogenic microorganisms, simultaneously and longitudinally, in the lung. This bedside method will ultimately enable physicians to rapidly, noninvasively, and accurately diagnose degrading lung and/or fibrosis without the need of OLBs. Objectives and Methods: To extend the information provided by standard imaging of the ARDS lung with a bedside, high-resolution, miniaturized pCLE through the detailed molecular imaging of a carefully selected region-of-interest (ROI). To validate and quantify real-time imaging to validate pCLE against OLB. Results: Developments in lung pCLE using fluorescent affinity- or activity-based probes at both preclinical and clinical (first-in-man) stages are ongoing—the results are promising, revealing correlations with OLBs in problematic ARDS. Conclusion: It can be envisaged that safe, high-resolution, noninvasive pCLE with activatable fluorescence probes will provide a “virtual optical biopsy” and will provide decisive information in selected ARDS patients at the bedside.

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Rahadi, Putu Suta Adya Dharma, Putu Widiadnyana, and Nengah Sweden. "Designing Data Warehouse in Finance Company Study at PT ABC." International Journal of Engineering and Emerging Technology 2, no. 1 (2017): 58. http://dx.doi.org/10.24843/ijeet.2017.v02.i01.p12.

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Along with the development of technology and business needs that are more advanced, the more effective and efficient uses of Information Systems is an important thing for companies to continue competing in the era of globalization. Every company wants an appropriate Information System to run business activities smoothly. Using data warehouses can help PT ABC's problems in accommodating large amounts of data with its OLTP system which can then be processed in determining future strategies through OLAP systems. So as to get the reports needed in maintaining the consistency and improve the performance of the company.

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Саринова, Асия Жумабаевна, та Татьяна Ивановна Третьякова. "ОСНОВНЫЕ ОСОБЕННОСТИ СОВРЕМЕННЫХ БАЗ ДАННЫХ ОБЕСПЕЧИВАЮЩИЕ ПРОМЫШЛЕННЫЕ РЕШЕНИЯ ГЛОБАЛЬНЫХ СЕРВИСОВ". Bulletin of Toraighyrov University. Energetics series, № 2,2021 (24 червня 2021): 155–65. http://dx.doi.org/10.48081/zmmx4346.

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Работа посвящена описанию основных особенностей современных баз данных, обеспечивающие промышленные решения глобальных сервисов. В статье был представлен рейтинг баз данных, который определил данное исследование. Произведен анализ баз данных OLAP и OLTP, а также современных базы данных, использующие хранилища данных таких социальных сетей, как Instagram, Facebook. Проведенные исследования доказывают что, промышленные решения на базе Cassandra широко распространены для обеспечения сервисов таких компаний, как Cisco, IBM, Cloudkick, Reddit, Digg, Rackspace, Apple, Twitter и Spotify. В результате исследований выявлены определенные преимущества и недостатки системы управления базами данных Cassandra, которые позволили отличить высокую степень масштабируемости, удовлетворяющая огромными данными и требовательными к производительности сценарии ее использования.

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Mohammed Omer Shakeel Ahmed. "Enhancing CRM Decision-Making with HTAP: Leveraging Real-Time Analytics for Competitive Advantage." Journal of Information Systems Engineering and Management 10, no. 23s (2025): 50–57. https://doi.org/10.52783/jisem.v10i23s.3675.

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Customer Relationship Management (CRM) systems traditionally separate transactional and analytical data into distinct layers, with transactional databases optimized for fast writes and analytical data warehouses for read-heavy queries. This separation introduces delays in analytics, hindering real-time insights and timely decision-making. Hybrid Transactional/Analytical Processing (HTAP) offers a unified solution by integrating Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) in a single system. This paper explores the feasibility of applying HTAP in CRM systems, highlighting its potential to enable real-time analytics, improve decision-making, and enhance business agility, while addressing associated challenges

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Sun, Lei, Hong Mei Xing, and Wei Wang. "Basic Technology of OLAP." Advanced Materials Research 1030-1032 (September 2014): 1892–95. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1892.

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s.The technology and principle involved in the on-line analytical processing is presented in theory, such as an overview of the on-line analytical technology, the operation of the on-line analytical technology, etc, which sets a technological foundation to build a system to realize online analysis.

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Sharma, Pitambar, and Piyush Girdhar. "Online Analytical Processing (OLAP)." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 1, no. 3 (2014): 01–04. http://dx.doi.org/10.53555/nncse.v1i3.520.

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This paper is basically accustomed define On-Line Analytical method (OLAP), WHO uses it and why, and to review the key choices required for OLAP code. On-Line Analytical method (OLAP) could also be a category of code technology that allows analysts, managers and executives to appreciate insight into info through fast, consistent, interactive access to an honest reasonably gettable views of {data of information} that has been transformed from data to mirror spatiality of the enterprise as understood by the user. whereas OLAP systems have the ability to answer "who?" and "what?" queries, it's their ability to answer "what if?" and "why?" that sets them except info Warehouses. OLAP applications span a variety of structure functions. Finance departments use OLAP for applications like budgeting, activity-based accountancy (allocations), cash performance analysis, and cash modelling. Sales analysis and prognostication square measure a pair of the OLAP applications found in sales departments. Among totally different applications, promoting departments use OLAP for analysis, sales prognostication, promotions analysis, consumer analysis, and market/customer segmentation. Typical manufacturing OLAP applications embody production coming up with and defect analysis. Although OLAP applications square measure found in wide divergent sensible areas, all of them want the following key choices like 3-D views of information, Calculation –intensive capabilities and Time Intelligence.

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Kuijpers, Bart, and Alejandro Vaisman. "An algebra for OLAP." Intelligent Data Analysis 21, no. 5 (2017): 1267–300. http://dx.doi.org/10.3233/ida-163161.

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Barghoorn, Martin. "Crosstab, OLAP, and APL." ACM SIGAPL APL Quote Quad 29, no. 3 (1999): 110–13. http://dx.doi.org/10.1145/327600.327627.

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Hudomalj, Emil, and Gaj Vidmar. "OLAP and bibliographic databases." Scientometrics 58, no. 3 (2003): 609–22. http://dx.doi.org/10.1023/b:scie.0000006883.28709.d2.

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Porobic, Danica, Ippokratis Pandis, Miguel Branco, Pınar Tözün, and Anastasia Ailamaki. "OLTP on hardware islands." Proceedings of the VLDB Endowment 5, no. 11 (2012): 1447–58. http://dx.doi.org/10.14778/2350229.2350260.

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