Document-oriented database

About: Document-oriented database is a research topic. Over the lifetime, 43 publications have been published within this topic receiving 216 citations. The topic is also known as: document store.

A qualitative analysis of the performance of MongoDB vs MySQL database based on insertion and retriewal operations using a web/android application to explore load balancing — Sharding in MongoDB and its advantages

Abstract: Our world has evolved to an optimal point of advancement. The extravagant growth has helped in the invention of technologies, industry standards, gadgets, and devices that produce enormous amount of data that all require an essential data management and manipulation system. The data acquired from the various input and output sources are indulged in providing a certain infrastructure are also susceptible to damages if not treated well which may result in loss of data. To overcome this loss, various strategies that run parallel to prevent such loss are being used, one such example is the NoSQL MongoDB. MongoDb is a cross-platform, document oriented database that provides, high performance and easy scalability ensuring effective data management with its prominent feature of auto sharding. Sharding splits the database across multiple servers, increasing the capacity and scalability as required. This feature handles distribution of data in different nodes to maximize disk space and dynamically load balance queries. Partitioning the databases appropriately is a major step that determines the efficiency of sharding. This involves choosing an index of the MongoDB, competently as a shared key for further horizontal scaling of the database. Our current research involves the study of this load balancer. This paper intends to ascertain the need for NoSQL databases in the present situation and emphasize advancement of document-oriented database — MongoDB in particular by describing with a quantitative example that SQL databases are prone to deterioration when data is over loaded and MongoDB comes with inbuilt load balancer which makes it a better solution in applications with high data load. We describe the technology of sharding — auto load balancing feature of MongoDB and hope to provide a comprehensive insight of the process.

Comparison of Relational Database with Document-Oriented Database (MongoDB) for Big Data Applications

Abstract: Database can accommodate a very large number of users on an on-demand basis. The main limitations with conventional relational database management systems (RDBMS) are that they are hard to scale with Data warehousing, Grid, Web 2.0 and Cloud applications, have non-linear query execution time, have unstable query plans and have static schema. Even though RDBMS's have provided database users with the best mix of simplicity, robustness, flexibility, performance, scalability and compatibility but they are not able to satisfy the present day users and applications for the reasons mentioned above. The next generation NonSQL (NoSQL) databases are mostly non-relational, distributed and horizontally scalable and are able to satisfy most of the needs of the present day applications. The main characteristics of these databases are schema-free, no join, non-relational, easy replication support, simple API and eventually consistent. The aim of this paper is to illustrate how a problem being solved using MySQL will perform when MongoDB is used on a Big data dataset. The results are encouraging and clearly showcase the comparisons made. Queries are executed on a big data airlines database using both MongoDB and MySQL. Select, update, delete and insert queries are executed and performance is evaluated.

Performance evaluation for CRUD operations in asynchronously replicated document oriented database

Abstract: NoSQL databases are becoming increasingly popular as more developers seek new ways for storing information. The popularity of these databases has risen due to their flexibility and scalability needed in domains like Big Data and Cloud Computing. This paper examines asynchronous replication, one of the key features for a scalable and flexible system. Three of the most popular Document-Oriented Databases, MongoDB, CouchDB, and Couchbase, are examined. For testing, the execution time for CRUD operations for a single database instance and for a distributed environment with two nodes is taken into account and the results are compared with tests outcomes obtained for three relational database management systems: Microsoft SQL Server, MySQL, and PostgreSQL.

Performance Evaluation for CRUD Operations in Asynchronously Replicated Document Oriented Database

Abstract: NoSQL databases are becoming increasingly popular as more developers seek new ways for storing information. The popularity of these databases has risen due to their flexibility and scalability needed in domains like Big Data and Cloud Computing. This paper examines asynchronous replication, one of the key features for a scalable and flexible system. Three of the most popular Document-Oriented Databases, Mongo DB, CouchDB, and Couch base, are examined. For testing, the execution time for CRUD operations for a single database instance and for a distributed environment with two nodes is taken into account and the results are compared with tests outcomes obtained for three relational database management systems: Microsoft SQL Server, MySQL, and Postgre SQL.

The Nunaliit Cybercartographic Atlas Framework

Abstract: This chapter describes the development of the Nunaliit Cybercartographic Atlas Framework and the significant changes that have taken place over the 10 years it has been under development. Three major challenges for the Framework are identified and some recent developments to respond to these are described. The chapter concludes by considering the future development of Nunaliit.