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CloudDBGuard: A framework for encrypted data storage in nosql wide column stores

DATA & KNOWLEDGE ENGINEERING 2020年 126卷 101732-101732页

作者： Wiese, Lena Waage, Tim Brenner, Michael Leibniz Univ Hannover Knowledge Based Syst Grp L3S Res Ctr Appelstr 4 D-30167 Hannover Germany Univ Goettingen Inst Comp Sci Goldschmidtstr 7 D-37077 Gottingen Germany Leibniz Univ Hannover Computat Hlth Informat Schlosswender Str 5 D-30159 Hannover Germany

Nowadays, cloud storage providers are widely used for outsourcing data. These remote cloud servers are not trustworthy when storing sensitive data. In this article we focus on the use case of storing data in a cloud database using a particular sub-category of nosql databases - so-called wide column stores. Unfortunately security was not a primary concern of the nosql systems designers. Using encryption before outsourcing the data can provide security. Conventional encryption however limits the options for interaction because the encrypted data lacks properties of the plaintext data that the database systems rely on. Various schemes have been proposed for property-preserving encryption in order to overcome these issues, allowing a database to process queries over encrypted data. In this article we comprehensively present details of our framework CloudDBGuard that allows using property-preserving encryption in unmodified wide column stores. It hides the complexity of the encryption and decryption process and allows various adjustments on specific use cases in order to achieve a maximum of security, functionality and performance.

关键词： Property-preserving encryption nosql databases Wide Column Stores

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Haery: A Hadoop Based Query System on Accumulative and High-Dimensional Data Model for Big Data

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2020年第7期32卷 1362-1377页

作者： Song, Jie He, HongYan Thomas, Richard Bao, Yubin Yu, Ge Northeastern Univ Software Coll Shenyang 110819 Liaoning Peoples R China Univ Queensland Sch Informat Technol & Elect Engn Brisbane Qld Australia Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Liaoning Peoples R China

Column-oriented stores, known for their scalability and flexibility, are a common nosql database implementation and are increasingly used in big data management. In column-oriented stores, a "full-scan" query strategy is inefficient and the search space can be reduced if data is well partitioned or indexed;however, there is no pre-defined schema for building and maintaining partitions and indexes at lower cost. We leverage an accumulative and high-dimensional data model, a sophisticated linearization algorithm, and an efficient query algorithm, to solve the challenge of how a pre-defined and well-partitioned data model can be applied to flexible and time-varied key-value data. We adapt a high-dimensional array as the data model to partition the key-value data without additional storage and massive calculation;improve the Z-order linearization algorithm, which map multidimensional data to one dimension while preserving locality of the data points, for flexibility;efficiently build an expansion mechanism for the data model to support time-varied data. The result is Haery, a column-oriented store, based on a distributed file system and computing framework. In experiments, Haery is compared with Hive, HBase, Cassandra, MongoDB, PostgresXL, and HyperDex in terms of query performance. With results indicating Haery on average performs 4.57x, 4.23x, 3.55x, 1.79x, 1.82x, and 120.6x faster, respectively.

关键词： Data models Big Data Partitioning algorithms nosql databases Indexing Key-value data column-oriented store multi-dimensional data model linearization accumulation

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A performance comparison of SQL and nosql databases

A performance comparison of SQL and NoSQL databases

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

作者： Li, Yishan Manoharan, Sathiamoorthy Univ Auckland Dept Comp Sci Auckland 1 New Zealand

ISBN: (纸本)9781479915019

With the current emphasis on "Big Data", nosql databases have surged in popularity. These databases are claimed to perform better than SQL databases. In this paper we aim to independently investigate the performance of some nosql and SQL databases in the light of key-value stores. We compare read, write, delete, and instantiate operations on key-value stores implemented by nosql and SQL databases. Besides, we also investigate an additional operation: iterating through all keys. An abstract key-value pair framework supporting these basic operations is designed and implemented using all the databases tested. Experimental results measure the timing of these operations and we summarize our findings of how the databases stack up against each other. Our results show that not all nosql databases perform better than SQL databases. Some are much worse. And for each database, the performance varies with each operation. Some are slow to instantiate, but fast to read, write, and delete. Others are fast to instantiate but slow on the other operations. And there is little correlation between performance and the data model each database uses.

关键词： Database performance SQL nosql databases

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Review of nosql databases and Performance Testing on HBase

Review of NoSQL Databases and Performance Testing on HBase

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International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)

作者： Naheman, Wumuti Wei, Jianxin Xinjiang Univ Coll Resources & Environm Sci Urumqi Peoples R China Xinjiang Land Resources Dept Informat Ctr Urumqi Peoples R China

ISBN: (纸本)9781479925650

nosql (Not Only SQL) is the generic term of a kind of non-relational database products. This paper, firstly, lists the disadvantages of traditional relational databases, introduces nosql databases including their advantages, disadvantages and their application status. Then, a comparison is made between nosql databases and SQL database, also another comparison between different nosql products. Finally, we introduce the architecture and data model of HBase database, which is a representative of nosql databases, and did some performance tests on HBase database, including the column family test, the sort test, the random read/write test and the query test. Test results show that written and query speed of HBase is slow under a single machine environment, but can be significantly improved in multi machine cluster environment.

关键词： relational database nosql databases HBase performance testing

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Column-oriented data model for data-intensive systems

Column-oriented data model for data-intensive systems

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Computer Science (COMSCI), International Scientific Conference on

作者： Simeon Emanuilov Aleksandar Dimov Department of Software Technologies Faculty of Mathematics and Informatics Sofia University “St. Kliment Ohridski”5 James Bourchier Blvd Sofia Bulgaria

ISBN: (数字)9781665497770

ISBN: (纸本)9781665497787

Traditional relational row-oriented databases have some performance issues in the case of data-intensive systems that process large amounts of data. On the other hand, a column-oriented approach to data presentation has shown promising results when applied in analytical processing. This paper shows a design for a webhook (event notifications) software system to facilitate the usage of the columnar approach in data-intensive software systems. It will be an example of using the column store where the analytical requirement is not the primary one. The approach can be applied to any system in the data-intensive context, which has many data points and requirements to store, fetch, and aggregate based on a few specific from many fields.

关键词： Computer science Adaptation models databases nosql databases Aggregates Computer architecture Benchmark testing

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An overview of data integration principles for heterogeneous databases

An overview of data integration principles for heterogeneous...

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Proceedings of the International Convention MIPRO

作者： Aleksandar Stojanović Marko Horvat Ž eljko Kovač ević Department of Informatics and Computer Science Zagreb University of Applied Sciences Zagreb Croatia Department of Applied Computing University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9789532331035

ISBN: (纸本)9781665484343

Modern large-scale information systems often use multiple database management systems, not all of which are necessarily relational. In recent years, nosql databases have gained acceptance in certain domains while relational databases remain de facto standard in many others. Many "legacy" information systems also use relational databases. Unlike relational database systems, nosql databases do not have a common data model or query language, making it difficult for users to access data in a uniform manner when using a combination of relational and nosql databases or simply several different nosql database systems. Therefore, the need for uniform data access from such a variety of data sources becomes one of the central problems for data integration. In this paper we provide an overview of the main problems, methods, and solutions for data integration between relational and nosql databases, as well as between different nosql databases. We focus mainly on the problems of structural, syntactic, and semantic heterogeneity and on proposed solutions for uniform data access, emphasizing some of the more recent proposals.

关键词： nosql databases Soft sensors Semantics Data integration Relational databases Writing Syntactics

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Development a Teleconsultation Platform for Outpatients during the COVID-19 Pandemic based on Cloud Firestore and Realtime databases

Development a Teleconsultation Platform for Outpatients duri...

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Biomedical Engineering International Conference (BMEiCON)

作者： Khanista Namee Korapin Infueng Jantima Polpinij Orrawan Suwittayapun Phattaraporn Promsurapat Areej Meny Faculty of Industrial Technology and Management King Mongkut’s University of Technology North Bangkok Bangkok Thaialnd Department of Computer Science Faculty of Informatics Intellect Laboratory Mahasarakham University Mahasarakham Thailand Chaophraya Abhaibhubejhr Hospital Ministry of Public Health Prachinburi Thailand Collage of Applied Medical Sciences King Saud bin Abdulaziz University for Health Sciences Jeddah Saudi Arabia

ISBN: (纸本)9781665489041

Due to the global epidemic situation of the Coronavirus Disease 2019 (Covid-19), in addition to serving patients with suspected symptoms and sickness from COVID-19, the hospital also provides services to patients outside requiring a lot of treatment causing a large number of queues in patients. It takes a long time to wait to see the doctor. The researcher therefore developed a teleconsultation platform. Hence, that patients can talk or seek advice from a doctor without the need to go to the hospital, allow patients to schedule appointments to see a doctor. Also, the patient can talk to the doctor via video calling developed in the system. Moreover, doctors can dispense medicines to patients by mail. To increase the efficiency of the system more and to support a wide range of applications, any devices, real-time data updates, appointment notification via chatbot using Cloud Firestore and Realtime databases, a nosql database, and study the performance gained. The results obtained from the test were satisfactory, with an average tracing server response of 107 ms + 0.14%, and an average handling latency in Thailand at 108 ms.

关键词： COVID-19 Performance evaluation Schedules Hospitals databases nosql databases Medical services

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Comparative analysis of embedded databases performance on single board computer systems using Python

Comparative analysis of embedded databases performance on si...

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International Computer Sciences and Information Technologies (CSIT)

作者： Marian Slabinoha Stepan Melnychuk Iryna Manuliak Bohdan Pashkovskyi Computer Systems and Networks Department Ivano-Frankivsk national technical university of oil and gas Ivano-Frankivsk Ukraine

ISBN: (纸本)9798350334326

The article deals with comparative analysis of SQL and nosql embedded databases performance on single-board computer systems, such as SQLite, LMDB and UnQLite. The aim of the article is to perform comparative testing of CRUD operations performance through database connection software implemented using Python, on single-board computer systems that need to store data in local storage without continuous running of database server process in system tray. The analysis of the related publications was done and the aim of work was set. The hardware and software was chosen to hold the experiment. The experiment details were described. The results were obtained, highlighting strong and weak features of SQL and nosql databases as well as key-value stores. Received results can be used when designing Python software for single-board computers with ability to store large amount of data in device local memory.

关键词： Performance evaluation databases nosql databases Memory management Software Hardware Servers

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CH3: A Mixed Workload Benchmark for Scalable nosql

CH3: A Mixed Workload Benchmark for Scalable NoSQL

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IEEE International Conference on Big Data

作者： Mehnaz Tabassum Mahin Bo-Chun Wang Kamini Jagtiani Michael Carey Keshav Murthy University of California Riverside Couchbase Inc. University of California Irvine

ISBN: (纸本)9781665480468

Database management systems that support hybrid workloads (i.e., HTAP or HOAP) first arose in the relational world. Such hybrid data management support in the document database (nosql) world is also gaining popularity in both commercial and research arenas. The CH2 benchmark was proposed in 2021 to evaluate such hybrid nosql platforms. In addition to operational and analytical services, full-text search is a key component of nosql platforms that provides a search engine-like query processing capability on JSON documents. In this paper, we present CH3, a mixed workload benchmark for evaluating scalable nosql platforms with OLTP, OLAP, and full-text search (FTS) workloads. Like CH2, the CH3 benchmark borrows from and extends both TPC-C and TPC-H. However, CH3 generates meaningful text content and includes FTS indexes and FTS queries on these indexes to model an FTS workload. This paper presents the required extensions from CH2 to address FTS workloads, the detailed design of CH3, and performance results obtained by running the CH3 benchmark against Couchbase Server (which offers Query, Analytics, and Search Services). The results provide insight into the performance of the Search Service, the performance isolation among OLTP, OLAP and FTS workloads, and the horizontal scalability of Couchbase Server as well as the effectiveness of CH3 for evaluating the mixed workload performance of such nosql platforms.

关键词： Analytical models Scalability Query processing nosql databases Benchmark testing Big Data Market research

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A Privacy-Preserving Model for Big Data

A Privacy-Preserving Model for Big Data

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Japan-Egypt International Conference on Electronics, Communications and Computers (JEC-ECC)

作者： Amr Morad Mohamed S. Abougabal Ayman Khalafallah Computer and Systems Engineering Alexandria University Alexandria Egypt

ISBN: (纸本)9781665464642

In the past few years, the tremendous expansion in the usage of computer programs has resulted in a large amount of data, called “Big Data.” This leads to new challenges for storage, processing, and privacy-preserving. Meanwhile, organizations tend to collect more data about customers for subsequent processing to extract knowledge, resulting in potential threats to their confidentiality. This raises significant questions regarding the security and privacy of data in nosql databases. In this paper, a privacy-preserving model for big data protection is proposed, which could be applied to various types of nosql databases. This model addresses the challenges of securing nosql databases including the lack of predefined schema, the existence of different nosql database categories, and the potential threats due to data processing. It also guarantees properties of conditional roles, purposes, tasks, policies, and possible insider threats. Verification and validation for the model using a use case are introduced to demonstrate how it ensures privacy-preserving in nosql databases.

关键词： Data privacy nosql databases Standards organizations Organizations Big Data Feature extraction Data processing

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