Database Vendors Research Articles

Hidden Inequities of Access

Despite ongoing efforts to improve database accessibility, aggregated database vendors concede that they do not have complete control over document accessibility. Instead, they point to the responsibility of journal publishers to deliver articles in an accessible format. This may increase the likelihood that users with disabilities will encounter articles that are not compatible with a screen reader. To better understand the extent of the problem, a document accessibility audit was conducted of randomly selected articles from EBSCO’s Library & Information Source database. Full-text articles from 12 library science journals were evaluated against two measures of screen reader compatibility: HTML format (the optimal format for screen readers) and PDF accessibility conformance. Findings showed inconsistencies in HTML format availability for articles in the selected journals. Additionally, the entire sample of PDF articles failed to meet the minimum standard of PDF Universal Accessibility of containing a tagged structure. However, all PDF articles passed accessibility permissions tests, so could be made accessible retroactively by a third party.

Eigen: End-to-End Resource Optimization for Large-Scale Databases on the Cloud

Increasingly, cloud database vendors host large-scale geographically distributed clusters to provide cloud database services. When managing the clusters, we observe that it is challenging to simultaneously maximizing the resource allocation ratio and resource availability. This problem becomes more severe in modern cloud database clusters, where resource allocations occur more frequently and on a greater scale. To improve the resource allocation ratio without hurting resource availability, we introduce Eigen, a large-scale cloud-native cluster management system for large-scale databases on the cloud. Based on a resource flow model, we propose a hierarchical resource management system and three resource optimization algorithms that enable end-to-end resource optimization. Furthermore, we demonstrate the system optimization that promotes user experience by reducing scheduling latencies and improving scheduling throughput. Eigen has been launched in a large-scale public-cloud production environment for 30+ months and served more than 30+ regions (100+ available zones) globally. Based on the evaluation of real-world clusters and simulated experiments, Eigen can improve the allocation ratio by over 27% (from 60% to 87.0%) on average, while the ratio of delayed resource provisions is under 0.1%.

Causality Between Firm-Level Governance and Firm Value

This paper investigates empirically whether there is a causal relation between firm-level governance and firm value. The firm-level governance quality is quantified by using anti-takeover provisions, which are classified boards, fair price, and poison pill. The firm value is measured by Tobin’s Q and return on assets in the part of Robustness Check. The data was found in platform WRDS, with database vendors of Compustat and Institutional shareholder services (ISS), ranged from 1998 to 2006, after data matching and data cleaning, with 1645 left. The regression results indicate that there is causality between firm-level governance and firm value, specifically that poor governance significantly contributes to the reduction of firm value. The robustness check has certified that the results in the regression analysis are credible. Further research will be desirable for firm data from countries such as China. In addition, the range of observation years of the data is expected to expand as data vendors have increased authority to access to the data.

Think outside the search box: A comparative study of visual and form-based query builders

Knowledge workers such as healthcare information professionals, legal researchers and librarians need to create and execute search strategies that are comprehensive, transparent and reproducible. The traditional solution is to use proprietary query-building tools provided by literature database vendors. In the majority of cases, these query builders are designed using a form-based paradigm that requires the user to enter keywords and ontology terms on a line-by-line basis and then combine them using Boolean operators. However, recent years have witnessed significant changes in human–computer interaction technologies, and users can now engage with online information systems using a variety of novel data visualisation techniques. In this article, we evaluate a new approach to query building in which users express concepts as objects on a visual canvas and compare this with a traditional form-based query builder in a laboratory-based user study. The results demonstrate the potential of visual interfaces to mitigate some of the shortcomings associated with form-based interfaces and encourage more exploratory search behaviour. They also demonstrate the value of having a temporary ‘scratch’ space in query formulation. In addition, the findings highlight an ongoing need for transparency and reproducibility in professional search and raise further questions about how these properties may best be supported.

Cloud databases

As database vendors are increasingly moving towards the cloud data service, i.e., databases as a service (DBaaS), cloud databases have become prevalent. Compared with the early cloud-hosted databases, the new generation of cloud databases, also known as cloud-native databases, seek for higher elasticity and lower cost by developing new techniques, e.g., compute-storage disaggregation and the log is the database. To better harness the power of these cloud databases, it is important to study and compare the pros and cons of their key techniques. In this tutorial, we offer a comprehensive survey of cloud-native databases. Based on various system architectures, we introduce a taxonomy for the state-of-the-art cloud-native OLTP databases and OLAP databases, respectively. We then take a deep dive into their key techniques regarding storage management, transaction processing, analytical processing, data replication, serverless computing, database recovery, and security. Finally, we discuss the research challenges and opportunities.

Insights Gained Through the Experience of Validation Studies of Outcomes and Future Initiatives as a Database Vendor

Insights Gained Through the Experience of Validation Studies of Outcomes and Future Initiatives as a Database Vendor

Data dependencies for query optimization: a survey

Effective query optimization is a core feature of any database management system. While most query optimization techniques make use of simple metadata, such as cardinalities and other basic statistics, other optimization techniques are based on more advanced metadata including data dependencies, such as functional, uniqueness, order, or inclusion dependencies. This survey provides an overview, intuitive descriptions, and classifications of query optimization and execution strategies that are enabled by data dependencies. We consider the most popular types of data dependencies and focus on optimization strategies that target the optimization of relational database queries. The survey supports database vendors to identify optimization opportunities as well as DBMS researchers to find related work and open research questions.

Filling the Gap in Database Usability

Library database vendors often revamp simpler interfaces of their database platforms with script-enriched interfaces to make them more attractive. Sadly, these enhancements often overlook users who rely on assistive technology, leaving electronic content difficult for this user base despite the potential of electronic materials to be easier for them to access and read than print materials. Even when providers are somewhat aware of this user group's needs there are questions about the effect of their efforts to date and whether accessibility documentation from them can be relied upon. This study examines selected vendors’ VPAT reports (Voluntary Product Accessibility Template) through a manual assessment of their database platforms to determine their overall accessibility.

MEASURING PERFORMANCE OF DATABASE SYSTEMS FOR APPLICATIONS OF IOT

Choosing the right database platform(s) for IoT solutions is daunting. First, IoT solutions can be distributed across geographical regions. As opposed to a centralized cloud-based solution, more solutions are adopting a combination of fog computing at the edge and cloud computing. As such, your database platforms must offer you the flexibility to process the data at the edge and synchronize between the edge servers and the cloud. Second, depending on your IoT use cases, the capabilities you want in your database could range from real-time data streaming, data filtering and aggregation, near-zero latency read operations, instant analytics, high availability, geo distribution, schema flexibility and so on. This article walks you through the four steps in choosing the right database platforms for your IoT solutions. The amount of data stored in IoT databases increases as the IoT applications extend throughout smart city appliances, industry and agriculture. Contemporary database systems must process huge amounts of sensory and actuator data in real-time or interactively. Facing this first wave of IoT revolution, database vendors struggle day-by-day in order to gain more market share, develop new capabilities and attempt to overcome the disadvantages of previous releases, while providing features for the IoT.

Native JSON datatype support

Both RDBMS and NoSQL database vendors have added varying degrees of support for storing and processing JSON data. Some vendors store JSON directly as text while others add new JSON type systems backed by binary encoding formats. The latter option is increasingly popular as it enables richer type systems and efficient query processing. In this paper, we present our new native JSON datatype and how it is fully integrated with the Oracle Database ecosystem to transform Oracle Database into a mature platform for serving both SQL and NoSQL style access paradigms. We show how our uniquely designed Oracle Binary JSON format (OSON) is able to speed up both OLAP and OLTP workloads over JSON documents.

Designing the Structured Search Experience: Rethinking the Query-Builder Paradigm

Knowledge workers such as healthcare information professionals, legal researchers, and librarians need to create and execute search strategies that are comprehensive, transparent, and reproducible. The traditional solution is to use command-line query builders offered by proprietary database vendors. However, these are based on a paradigm that dates from the days when users could access databases only via text-based terminals and command-line syntax. In this paper, we present a new approach in which users express concepts as objects on a visual canvas and manipulate them to articulate relationships. This offers a more intuitive user experience (UX) that eliminates many sources of error, makes the query semantics more transparent, and offers new ways to collaborate, share, and optimize search strategies and best practices

Polypharmacy in elderly patients in Japan: Analysis of Japanese real-world databases.

Polypharmacy is associated with an increased risk of adverse drug reactions (ADRs) and drug interactions, decreased adherence to medication and increased medical cost. Recently, polypharmacy has become a major problem in medical care in Japan as a result of the increase in the ageing population. The purpose of this study was to investigate the current situation of polypharmacy and the association between polypharmacy and adverse events. A retrospective data analysis was performed using two different real-world data from 2007 to 2015 in Japan. The Japanese Adverse Drug Event Report (JADER), a public spontaneous adverse drug reaction database constructed by the Pharmaceuticals and Medical Devices Agency (PMDA), and a large prescription database constructed by a database vendor (Japan Medical Information Research Institute, Inc Japan [JMIRI]) were analysed. Trends of polypharmacy during the study period were investigated. The mean number of drugs per report in the JADER database and per prescription in the JMIRI databases during the study period ranged from 4.8 to 5.6 and 3.5 to 3.7, respectively. The mean number of drugs increased with age in both the JADER and JMIRI databases, and the peak of the mean number of drugs was at 80-89years (5.74 drugs) in the JADER database and at 90-99years (4.97 drugs) in the JMIRI database. The number of drugs increased until age 90years or more, even though adverse events are more likely to occur after the age of 80 in Japan. Therefore, polypharmacy in the elderly should be focused on the patients aged ≥80years rather than patients aged ≥65years from the viewpoint of the prevention of adverse events.

A Narrative Review of Storing and Querying XML Documents Using Relational Database

Extensible Markup Language (XML) has become a common language for data interchange and data representation in the Web. The evolution of the big data environment and the large volume of data which is being represented by XML on the Web increase the challenges in effectively managing such data in terms of storing and querying. Numerous solutions have been introduced to store and query XML data, including the file systems, Object-Oriented Database (OODB), Native XML Database (NXD), and Relational Database (RDB). Previous research attempts indicate that RDB is the most powerful technology for managing XML data to date. Because of the structure variations of XML and RDB, the need to map XML data to an RDB scheme is increased. This growth has prompted numerous researchers and database vendors to propose different approaches to map XML documents to an RDB, translating different types of XPath queries to SQL queries and returning the results to an XML format. This paper aims to comprehensively review most cited and latest mapping approaches and database vendors that use RDB solution to store and query XML documents, in a narrative manner. The advantages and the drawbacks of each approach is discussed, particularly in terms of storing and querying. The paper also provides some insight into managing XML documents using RDB solution in terms of storing and querying and contributes to the XML community.

A Contemporary Methodology to Unify Structured Data in Portable Devices

The aim is to provide a methodology to handle Mobile Devices data using an ISAMD (Improved Synchronization Algorithm based on Secured Message Digest) so that data synchronization can take place between a mobile based database server and a multipurpose database. The ISAMD generates a Message Digest Table (MDT) in the database server. The secured Message Digest is used by the mobililty based database. This table stores the encoded format data put away by the client. These tables are contrasted push savvy all together with select the lines required for synchronization. On the off chance that and when any two lines of these MDT are extraordinary, the synchronization procedure advances as indicated by the synchronization strategy. The ISAMD algorithm does not utilize systems that are subject to explicit database merchants; may use triggers, put away methods or timestamps. The proposed algorithm utilizes just the normal SQL capacities for the synchronization. And the proposed algorithm possibly utilized for mixes of back-end storages and mobile databases due to its autonomy of database vendor. The encoded data in the database server can be decoded and retained based on end user request.

QTune

Database knob tuning is important to achieve high performance (e.g., high throughput and low latency). However, knob tuning is an NP-hard problem and existing methods have several limitations. First, DBAs cannot tune a lot of database instances on different environments (e.g., different database vendors). Second, traditional machine-learning methods either cannot find good configurations or rely on a lot of high-quality training examples which are rather hard to obtain. Third, they only support coarse-grained tuning (e.g., workload-level tuning) but cannot provide fine-grained tuning (e.g., query-level tuning). To address these problems, we propose a query-aware database tuning system QTune with a deep reinforcement learning (DRL) model, which can efficiently and effectively tune the database configurations. QTune first featurizes the SQL queries by considering rich features of the SQL queries. Then QTune feeds the query features into the DRL model to choose suitable configurations. We propose a Double-State Deep Deterministic Policy Gradient (DS-DDPG) model to enable query-aware database configuration tuning, which utilizes the actor-critic networks to tune the database configurations based on both the query vector and database states. QTune provides three database tuning granularities: query-level, workload-level, and cluster-level tuning. We deployed our techniques onto three real database systems, and experimental results show that QTune achieves high performance and outperforms the state-of-the-art tuning methods.

Assess the Changing Role of Database Technology within Geographic Information System Over the Past 45 Years

Spatial data stored in databases have been become progressively crucial in the geographic information system (GIS) field within recent years. Spatial data are increasingly being noted for its significance in representing for real-life relationships. The value of spatial databases cannot be underestimated since it has been established to be an efficient and flexible means of handling enormous spatial datasets. This paper shows the different methods, in which spatial data are integrated by major database vendors and database within GIS. The current report has also examined the new technologies and advancements by database and GIS vendors in relational database management systems in the past four decades, which have facilitated spatial data to become integrated into databases.

Database Systems Performance Evaluation for IoT Applications

The amount of data stored in IoT databases increases as the IoT applications extend throughout smart city appliances, industry and agriculture. Contemporary database systems must process huge amounts of sensory and actuator data in real-time or interactively. Facing this first wave of IoT revolution, database vendors struggle day-by-day in order to gain more market share, develop new capabilities and attempt to overcome the disadvantages of previous releases, while providing features for the IoT. There are two popular database types: The Relational Database Management Systems and No SQL databases, with No SQL gaining ground on IoT data storage.In the context of this paper these two types are examined. Focusing on open source databases, the authors experiment on IoT data sets and pose an answer to the question which one performs better than the other. It is a comparative study on the performance of the commonly market used open source databases, presenting results for the No SQL MongoDB database and SQL databases of MySQL and PostgreSQL.

EBSCO information services usability study on accessibility

PurposeLast spring, EBSCO Information Services conducted a usability study with several students with visual impairments. The goal was to understand how these students conduct research and identify areas for improvement of EBSCO Discovery Service™ such that it would meet the needs of all potential users. EBSCO Discovery Service™ provides users with means of accessing all of an institution’s internal (library) and external (database vendors) information resources through a single search. The purpose of this paper is to outline the findings of this research and the applicability to the design of any online resource.Design/methodology/approachUsing the Bentley University’s user experience lab to facilitate the study and the Carroll Center for the Blind in Newton, Massachusetts, for recruitment of college students, EBSCO solicited feedback on how students conduct research on the Web in general, as well as their experience using EBSCO’s discovery service. The study involved a structured interview with eight visually impaired students from the Boston area, who had recently been enrolled in a college course. The students were also asked to complete certain tasks using the discovery service and report out as they completed each activity.FindingsThe findings demonstrated that for the most part, students with visual impairments engaged in research on the Web and within the discovery service in a similar manner to sighted students. They used the same standard search sites, expected the same layout conventions for results’ lists and filters and wanted easily savable full-text documents. Main differences involved their ability to navigate in a similar way to sighted users. Elements that one could skip over quickly as a sighted user were more of a hindrance to those relying on a screen reader. Additionally, improved descriptions for graphics, functions and form fields were noted as opportunities for improvement. For those with low vision, using screen magnifiers, modal boxes and hover features or other unexpected changes on the site proved to be challenging.Research limitations/implicationsThis study focused only on students with visual disabilities. There are many other print disabilities that were not explored such as color blindness, cognitive disabilities or learning disabilities. All the students were in their 20s and had experience conducting research and using library or research-related search sites. Many of the findings highlighted areas of improvement that would benefit all students.Originality/valueA study on students with visual disabilities using assistive technologies as they completed research tasks on a discovery system has not been studied before. Guidelines and audits do not provide a complete picture as to whether a website is fully accessible. It is only by working with actual users that insight into what it means to create a truly accessible experience can be gained.

Database Systems Performance Evaluation for IoT Applications

The amount of data stored in IoT databases increases as the IoT applications extend throughout smart city appliances, industry and agriculture. Contemporary database systems must process huge amounts of sensory and actuator data in real-time or interactively. Facing this first wave of IoT revolution, database vendors struggle day-by-day in order to gain more market share, develop new capabilities and attempt to overcome the disadvantages of previous releases, while providing features for the IoT. There are two popular database types: The Relational Database Management Systems and No SQL databases, with No SQL gaining ground on IoT data storage.In the context of this paper these two types are examined. Focusing on open source databases, the authors experiment on IoT data sets and pose an answer to the question which one performs better than the other. It is a comparative study on the performance of the commonly market used open source databases, presenting results for the No SQL MongoDB database and SQL databases of MySQL and PostgreSQL.

Hedge fund index-engineering methodologies: a comparison and demonstration

ABSTRACTWe examine hedge fund (HF) index construction methodologies, by describing and analysing case studies from two well-known database vendors and evaluating them using numerical examples on the same dataset. Despite the fact that they follow a similar due diligence process, there are great differences in the index engineering practices arising from different quantitative techniques, even for indices in the same HF category. However, those quantitative techniques provide similar results. The differences are rather due to the use of different HF universes and different inclusion criteria. This article is the first to use actual numerical case studies to illustrate and compare how HF index engineering works. Having read it, the reader will have a good understanding of how HF indices are formed.