Master of Science / Department of Computing and Information Sciences / Doina Caragea / There are many formats in which digital information is stored in order to share and re-use it by different applications. The web can hardly be called old and already there is huge research going on to come up with better formats and strategies to share information. Ten years ago formats such as XML, CSV were the primary data interchange formats. And these formats were huge improvements over SGML (Standard Generalized Markup Language). It’s no secret that in last few years there has been a huge transformation in the world of data interchange. More lightweight, bandwidth-non-intensive JSON has taken over traditional formats such as XML and CSV. BigData is the next big thing in computer sciences and JSON has emerged as a key player in BigData database technologies. JSON is the preferred format for web-centric, “NoSQL” databases. These databases are intended to accommodate massive scalability and designed to store data which does not follow any columnar or relational model. Almost all modern programming languages support object oriented concepts, and most of the entity modeling is done in the form of objects. JSON stands for Java Script object notation and as the name suggests this object oriented nature helps modeling entities very naturally. And hence the exchange of data between the application logic and database is seamless. The aim of this report is to develop two similar applications, one with traditional SQL as the backend, and the other with a JSON supporting MongoDB. I am going to build real life functionalities and test the performance of various queries. I will also discuss other aspects of databases such as building a Full Text Index (FTI) and search optimization. Finally I will plot graphs to study the trend in execution time of insertion, deletion, joins and co- relational queries with and without indexes for SQL database, and compare them with the execution trend of MongoDB queries.

Midroc automation uses databases for many different projects, both internally and in customer projects. At present, they are mainly using relational databases. There is an interest in researching different types of databases not based on the relational model. Midroc automation wants to know if there are any advantages of using a non-relational database. This project will compare two different databases. To make this comparison Microsoft SQL and MongoDB has been selected. MongoDB is a document type database which belongs to the category of non-relational databases commonly referred to as NoSQL. An application with a GUI and CRUD operations for each database has been implemented. This implementation was done using C# .NET in Visual Studio. The result of the comparison shows that MongoDB is more flexible while developing a database. It is also easier to make changes to an existing database while working with MongoDB. It is however harder to find information and support online when working with MongoDB. / Midroc Automation använder databaser till många olika projekt, både internt och mot sina kunder. Idag använder de främst databaser baserade på relationsmodellen. De är intresserade av att utreda om det finns några andra typer av databaser som inte är baserade på relationsmodellen och också om dessa skulle innebära några fördelar. I detta projekt kommer man att jämföra två olika databaser. För att göra denna jämförelse har man valt att undersöka Microsoft SQL och MongoDB. MongoDB är en databas av dokumenttyp som tillhör de moderna icke-relationella databaserna kallade NoSQL. För att göra jämförelsen har en applikation med tillhörande GUI och CRUD-operationer implementerats för varje databas. Implementationen har gjorts med hjälp av C# .NET i utvecklingsverktyget Visual Studio. Resultatet av jämförelsen visar att MongoDB är mer flexibelt vid utveckling av databasen. Det är också enklare att göra ändringar till en befintlig databas med MongoDB. Det är dock svårare att hitta information och hjälp online då man utvecklar en Mongo databas.

NoSQL är ett omtalat ämne just nu. Det finns mycket som talar för att det ska lösa de problem relationsdatabaser lider av. Exempelvis onödigt resurskräavande system eller svårt att konvertera mellan olika format på data. Att lösa dessa problem är något Ida Infront är intresserade av för lagringen i deras ärendehanteringsplattform iipax. Uppgiften är att ta reda på vad NoSQL-begreppet faktiskt innebär och utvärdera utvalda databaser mot Ida Infront och iipax krav. Problemet har angripits genom en litteraturstudie av NoSQL för att sedan undersöka tre databaser: Neo4J, CouchDB och Cassandra. Implementationerna har undersökts för att ge en bättre bild av vad NoSQL innebär i praktiken. Resultatet av arbetet är att NoSQL är ett väldigt diffust begrepp där många är oense om vad som gäller. Det är några olika typer av databaser som räknas till NoSQL men de i sig är ingen definition av begreppet. Olika typer som ofta nämns är dokument, graf och kolumndatabaser. När det kommer till de specifika databaserna ser de ut att ha spännande egenskaper som kan passa iipax, till exempel bra datamodell eller stöd för fulltextindexering. Slutligen kan det sägas att Neo4J i dagsläget ser ut som den bästakandidaten för lagringen i iipax.

En databasmodell är en viktig del av en applikation och för företag som utvecklar molntjänster är det viktigt att databasmodellen kan hantera föränderlig och växande data. För mikroföretag som utvecklar molntjänster är val av databasmodell en stor investering. Ett medvetet val måste göras för att säkerställa att rätt databasmodell väljs utefter de förutsättningar, resurser och syfte man har med sin applikation. Då mikroföretag inte har samma resurser i form av kapital, kunskap och kompetens som större företag är detta val än mer viktigt. I denna uppsats har en kvalitativ undersökning genomförts i syfte att svara på två delfrågor och en huvudfråga. Delfrågorna skall ligga som grund till att svara på huvudfrågan i uppsatsen. Huvudfrågan ämnar identifiera vilka faktorer mikroföretag som utvecklar molntjänster bör beakta vid val avdatabasmodell för deras förutsättningar och syfte. Delfråga 1 ämnar identifiera vilka fördelar samt nackdelar som finns med databasmodellerna relationsdatabaser och NoSQL databaser. Delfråga 2 ämnar klargöra om det finns några faktorer som påverkar valet av databasmodell speciellt för en molntjänst. Resultatet av uppsatsen och den slutsats som arbetet resulterade i var att mikroföretag med hjälp av de för- och nackdelar som identifierats kan utvärdera vilken databasmodell som passar deras förutsättningar och syfte. Då syfte och förutsättningar skiljer sig mellan företag är detta en analys som de själva måste genomföra. Studien visade att finns vissa speciella aspekter att beakta för valet av databasmodell för en molntjänst men att det inte skiljer sig avsevärt från vilka aspekter som beaktas för val av databasmodeller i allmänhet.

While relational databases still hold the primary position in the database technology domain, and have been for the longest time of any Computer Science technology has since its inception, for the first time the relational databases now have valid and worthy opponent in the NoSQL database movement. NoSQL databases, even though not many people have heard of them, with a significant number of Computer Science people included, have spread rapidly in many shapes and forms and have done so in quite a chaotic fashion. Similarly to the way they appeared and spread, design and modeling for them have been undertaken in an unstructured manner. Currently they are subcategorized in 4 main groups as: Key-value stores, Column Family stores, Document stores and Graph databases. In this thesis, different modeling approaches for graph databases, applied to the same domain are analyzed and compared, especially from a design perspective. The database selected here as the implemented technology is Neo4J by Neo Technologies and is a directed property graph database, which means that relationships between its data entities must have a starting and ending (or source and destination) node. This research provides an overview of two competing modeling approaches and evaluates them in a context of a real world example. The work done here shows that both of these modeling approaches are valid and that it is possible to fully develop a data model based on the same domain data with both approaches and that both can be used later to support application access in a similar fashion. One of the models provides for faster access to data, but at a cost of higher maintenance and increased complexity.

Currently two major database management systems are in use for dealing with data, the Relational Database Management System (RDBMS) also knows as standard SQL databases and the NoSQL databases. The RDBMS databases deal with structured data and the NoSQL databases with unstructured or semi-structured data. The RDBMS databases have been popular for many years but the NoSQL type is gaining popularity with the introduction of the internet and social media. Data flow from SQL to NoSQL or vice versa is very much possible in the near future due to the growing popularity of the NoSQL databases. The goal of this thesis is to analyze the data structures of the RDBMS and the NoSQL databases and to suggest a Graphical User Interface (GUI) tool that migrates the data from SQL to NoSQL databases. The relational databases have been in use and have dominated the industry for many years. In contrast, the NoSQL databases were introduced with the increased usage of the internet, social media, and cloud computing. The traditional relational databases guarantee data integrity whereas high availability and scalability are the main advantages of the NoSQL databases. This thesis presents a comparison of these two technologies. It compares the data structure and data storing techniques of the two technologies. The SQL databases store data differently as compared to the NoSQL databases due to their specific demands. The data stored in the relational databases is highly structured and normalized in most environments whereas the data in the NoSQL databases are mostly unstructured. This difference of the data structure helps in meeting the specific demands of these two systems. The NoSQL DBs are scalable with high availability due to the simpler data model but does not guarantee data consistency at all times. On the other hand the RDBMS systems are not easily scalable and available at the same time due to the complex data model but guarantees data consistency. This thesis uses CouchDB and MySQL to represent the NoSQL and standard SQL databases respectively. The aim of the iii research in this document is to suggest a methodology for data migration from the RDBMS databases to the document-based NoSQL databases. Data migration between the RDBMS and the NoSQL systems is anticipated because both systems are currently in use by many industry leaders. This thesis presents a Graphical User Interface as a starting point that enables the data migration from the RDBMS to the NoSQL databases. MySQL and CouchDB are used as the test databases for the relational and NoSQL systems respectively. This thesis presents an architecture and methodology to achieve this objective.

Database is the important part of modern application. From SQL to RDBMS,database moved to frequently transmit and operate lots of data. On ACID, it is focus on the consistence, but it does not suit right now. In the proposed article, we use YCSB to try some different workloads and the special of Cassandra, MongoDB, HBase, and MySQL Cluster to find the difference between SQL and NoSQL. In addition, we also analyze the performance of the four operations (insert, update, scan, and read) in Cassandra, MongoDB, and HBase, and simulate some conditions. Those test supplies the reference for user to select the database.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / No presente resumen

Systems operating in a medical environment need to maintain high standards regarding availability and performance. Large amounts of images are stored and studied to determine what is wrong with a patient. This puts hard requirements on the storage of the images. In this thesis, ways of incorporating distributed storage into a medical system are explored. Products, inspired by the success of Google, Amazon and others, are experimented with and compared to the current storage solutions. Several “non-relational databases” (NoSQL) are investigated for storing medically relevant metadata of images, while a set of distributed file systems are considered for storing the actual images. Distributed processing of the stored data is investigated by using Hadoop MapReduce to generate a useful model of the images' metadata.

Sectra has a customer database with approximately 1600 customers across the world. In this system there exists not only medical information but alsoinformation about the environment which the system runs in, usage  pattern and much more. This report is about storing data received from log les into a suitable database. Sectra wants to be able to analyze this information so that they can make strategic decisions and get a better understanding of their customers' needs. The tested databases are MongoDB, Cassandra, and MySQL. The results shows that MySQL  is not suitable for storing large amount of data with the current conguration. On the other hand, both MongoDB and Cassandra performed well with the growing amount of data.