The End of a Myth: Distributed Transactions Can Scale

The common wisdom is that distributed transactions do not scale. But what if distributed transactions could be made scalable using the next generation of networks and a redesign of distributed databases? There would be no need for developers anymore to worry about co-partitioning schemes to achieve decent performance. Application development would become easier as data placement would no longer determine how scalable an application is. Hardware provisioning would be simplified as the system administrator can expect a linear scale-out when adding more machines rather than some complex sub-linear function, which is highly application specific. In this paper, we present the design of our novel scalable database system NAM-DB and show that distributed transactions with the very common Snapshot Isolation guarantee can indeed scale using the next generation of RDMA-enabled network technology without any inherent bottlenecks. Our experiments with the TPC-C benchmark show that our system scales linearly to over 6.5 million new-order (14.5 million total) distributed transactions per second on 56 machines.Comment: 12 page

Modelling and Simulation of a Decision Support System Prototype Built on an Improved Data Warehousing Architecture for the School of Postgraduate, MAUTECH, Yola – Nigeria

A Data Warehouse (DW) is constructed with the goal of storing and providing all the relevant information that is generated along the heterogeneous databases of an organization. The development and management of precise and up-to-date information concerning academic staff, department, faculty, student’s academic record etc. is critically important in the management of a university. This study has become necessary because, data warehousing is a new field, a small number of investigations has been done regarding the features of academic data analysis and report. At present, data warehousing is among the best solution for gathering and maintaining data for decision making.  Therefore, the aim of this paper is to develop a DW prototype model for the School of Postgraduate Studies’ (SPGS) programmes of Modibbo Adama University of Technology (MAUTEC), Yola. The objective of the study is to model and simulate a decision support system that is capable of querying the prototype DW database model to generate reports as output in order to help administrative decision making of the SPGS MAUTEC, Yola. The study has provided relevant literatures in relation to the subject matter. In the methodology, a secondary, field and case study research were conducted. The software engineering development methodology considered was the “Realistic Waterfall Model”. The findings of this paper provide a DW prototype database model using a dimensional modeling technique and the graphic user interface tool for reports and analysis. The researchers have demonstrated their understanding on the subject matter and as a matter of fact, possible future work has been suggested from where we stopped. Keywords - Data Warehouse, Modeling, Simulation, Prototype and Decision Support Syste

Logic Programming Applications: What Are the Abstractions and Implementations?

This article presents an overview of applications of logic programming, classifying them based on the abstractions and implementations of logic languages that support the applications. The three key abstractions are join, recursion, and constraint. Their essential implementations are for-loops, fixed points, and backtracking, respectively. The corresponding kinds of applications are database queries, inductive analysis, and combinatorial search, respectively. We also discuss language extensions and programming paradigms, summarize example application problems by application areas, and touch on example systems that support variants of the abstractions with different implementations

The Development of a Benchmark Tool for NoSQL Databases

The aim of this article is to describe a proposed benchmark methodology and software application targeted at measuring the performance of both SQL and NoSQL databases. These represent the results obtained during PhD research (being actually a part of a larger application intended for NoSQL database management). A reason for aiming at this particular subject is the complete lack of benchmarking tools for NoSQL databases, except for YCBS [1] and a benchmark tool made specifically to compare Redis to RavenDB. While there are several well-known benchmarking systems for classical relational databases (starting with the canon TPC-C, TPC-E and TPC-H), on the other side of databases world such tools are mostly missing and seriously needed

Location-aware Mobile Services for a Smart City: Design, Implementation and Deployment

A smart city is a high-performance urban context, where citizens are more aware of, and more integrated into the city life, thanks to an intelligent city information system. In this paper we design, implement and deploy a smart application that retrieves and conveys to the user relevant information on the user's surroundings. This case study application let us discuss the challenges involved in creating a location-aware mobile service based on live information coming from the city IT infrastructure. The service, that is currently being deployed in the Italian city of Cesena, has been designed with the goal of being a general model for future applications. In particular, we discuss location-aware and mobile development, cloud and cluster based geographical data storage, and spatial data computation. For each of these topics we provide implementation and deployment solutions based on currently available technology. In particular we propose an architecture based on a complex On-Line Transaction Processing (OLTP) infrastructure. Furthermore, this paper represents the first comprehensive, scientific study on the subject

A Survey on Graph Database Management Techniques for Huge Unstructured Data

Data analysis, data management, and big data play a major role in both social and business perspective, in the last decade. Nowadays, the graph database is the hottest and trending research topic. A graph database is preferred to deal with the dynamic and complex relationships in connected data and offer better results. Every data element is represented as a node. For example, in social media site, a person is represented as a node, and its properties name, age, likes, and dislikes, etc and the nodes are connected with the relationships via edges. Use of graph database is expected to be beneficial in business, and social networking sites that generate huge unstructured data as that Big Data requires proper and efficient computational techniques to handle with. This paper reviews the existing graph data computational techniques and the research work, to offer the future research line up in graph database management