Veronika Abramova

NoSQL databases: MongoDB vs cassandra

In the past, relational databases were used in a large scope of applications due to their rich set of features, query capabilities and transaction management. However, they are not able to store and process big data effectively and are not very efficient to make transactions and join operations. Recently, emerge a new paradigm, NoSQL databases, to overcome some of these problems, which are more suitable for the usage in web environments. In this paper, we describe NoSQL databases, their characteristics and operational principles. The main focus of this paper is to compare and evaluate two of the most popular NoSQL databases: MongoDB and Cassandra.

Testing Cloud Benchmark Scalability with Cassandra

NoSQL databases were developed as highly scalable databases that allow easy data distribution over a number of servers. With the increased interest of researchers and companies in non-relational technology, NoSQL databases became widely used and a common belief emerged defending that those engines scale well. This means that the use of more nodes would result in reduced execution time of requests and the system would scale adequately, by adding nodes proportionally to data size and load. However, sometimes, adding nodes may not result in improvement of request-serving time. Therefore, it is useful to investigate how different factors, such as workload, data size and number of simultaneous sessions influence scaling capabilities. We will review the architecture of Cassandra, which is known for being one of the most efficient NoSQL engines, and analyze its scalability, using the Yahoo Cloud Serving Benchmark. The results will allow a better understanding of scalability and scalability limitations in that type of environment.

NoSQL Databases: A Software Engineering Perspective

For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have started being developed, namely NoSQL technology. With increased interest in NoSQL technology, as well as more use case scenarios, over the last few years these databases have been more frequently evaluated and compared. It is necessary to find if all the possibilities and characteristics of non-relational technology have been disclosed. While most papers perform mostly performance evaluation using standard benchmarks, it is nevertheless important to notice that real world scenarios, with real enterprise data, do not function solely based on performance. In this paper, we have gathered a concise and up-to-date comparison of NoSQL engines, their most beneficial use case scenarios from the software engineer viewpoint, their advantages and drawbacks by surveying the currently available literature.

Open Source vs Proprietary Project Management Tools

The dimensional growth and increasing difficulty in project management promoted the development of different tools that serve to facilitate project management and track project schedule, resources and overall progress. These tools offer a variety of features, from task and time management, up to integrated CRM (Customer Relationship Management) and ERP (Enterprise Resource Planning) modules. Currently, a large number of project management software is available, to assist project team during the entire project lifecycle. We present the main differences between open source and proprietary project management tools, describing the key features and how those can assist the project manager and the development team. In this paper, we analyse three open-source project management tools: OpenProject, ProjectLibre, Redmine, and three proprietary tools: Bitrix24, JIRA, and Microsoft Project.

No SQL in Practice: A Write-Heavy Enterprise Application

The continuous information growth in current organizations has created a need for adaptation and innovation in the field of data storage. Alternative technologies such as NoSQL have been heralded as the solution to the ever-growing data requirements of the corporate world, but these claims have not been backed by many real world studies. Current benchmarks evaluate database performance by executing specific queries over mostly synthetic data. These artificial scenarios, then, prevent us from easily drawing conclusions for the real world and appropriately characterize the performance of databases in a real system. To counter this, we used a real world enterprise system with real corporate data to evaluate the performance characteristics of popular NoSQL databases and compare them to SQL counterparts. In particular, we present one of the first write-heavy evaluations using enterprise software and big data. We tested Cassandra, Mongo DB, Couchbase Server and MS SQL Server and compared their performance while handling demanding and large write requests from a real company with an electrical measurement enterprise system.

Evaluating Cassandra Scalability with YCSB

NoSQL data stores appeared to fill a gap in the database market: that of highly scalable data storage that can be used for simple storage and retrieval of key-indexed data while allowing easy data distribution over a possibly large number of servers. Cassandra has been pinpointed as one of the most efficient and scalable among currently existing NoSQL engines. Scalability of these engines means that, by adding nodes, we could have more served requests with the same performance and more nodes could result in reduced execution time of requests. However, we will see that adding nodes not always results in performance increase and we investigate how the workload, database size and the level of concurrency are related to the achieved scaling level. We will overview Cassandra data store engine, and then we evaluate experimentally how it behaves concerning scaling and request time speedup. We use the YCSB – Yahoo! Cloud Serving Benchmark for these experiments.

On the Use of CEP in Safety-critical Systems.

Safety-critical systems have to continuously manage risks, in order to handle hazardous situations and still be able to fulfil their purpose. While being composed by a variety of software, as well as hardware components, it is necessary for each part of these systems, alone and as a whole, to exhibit a required set of characteristics, necessary to ensure the correct system functioning. Complex Event Processing (CEP) systems have been used in a diversity of applications and, while they focus on fast data gathering and processing as well as in providing intelligence to their users, there is incomplete information about how they are adequate to integrate safety-critical systems. In this paper we investigate if the mainstream off-the-shelf CEP systems are suitable for safety-critical applications. We describe the use of complex event processing engines in safety-critical systems and how some authors enhance those to better correspond to the critical system requirements. We demonstrate that, although dependability is well handled in most CEP systems, the same cannot be assumed about security and safety attributes.

DNA Analysis: Principles and Sequencing Algorithms.

DNA discovery has put humans one step closer to deciphering their own structure stored as biological data. Such data could provide us with a huge amount of information, necessary for studying ourselves and learn all the variants that pre-determine ones characteristics. Although, these days, we are able to extract DNA from our cells and transform it into sequences, there is still a long road ahead since DNA has not been easy to process or even extract in one go. Over the past years, bioinformatics has been evolving more and more, constantly aiding biologists on the attempts to “break” the code. In this paper, we present some of the most relevant algorithms and principles applied on the analysis of our DNA. We attempt to provide basic genome overview but, moreover, the focus of our study is on assembly, one of the main phases of DNA analysis.

Ethic in Massively Multiplayer Online Role-Playing Games

Massively Multiplayer Online Role-Playing Game more known as MMORPG is a popular type of game played all over the globe. While being online people tend to change and so do their attitudes. But even there the concept of ethic exists and there are rules that should be followed. Even while still being a game, it is based on social activities and just like in society, code of conduct applies and misbehavior should be punished. This paper analyzes player interaction in online games and if there exist ethical behavior in MMORPGs environment.