This comprehensive hands-on guide presents fundamental concepts and practical solutions for getting you ready to use No SQL databases. In addition, they are often malleable and flexible enough to accommodate semi-structured and sparse data sets. Most No SQL databases scale well as data grows. Provides programmers with a complete foundation in My SQL, the multi-user, multi-threaded SQL database server that easily stores, updates, and accesses informationOffers detailed instructions for My SQL installation and configuration on either Windows or LinuxShows how to create a database, work with SQL, add and modify data, run queries, perform administrative tasks, and build database applicationsDemonstrates how to connect to a My SQL database from within PHP, Java, ASP, and ASP.NET applicationsCompanion Web site includes SQL statements needed to create and populate a database plus three readyĪ hands-on guide to leveraging No SQL databases No SQL databases are an efficient and powerful tool for storing and manipulating vast quantities of data. The result of this work can provide some guideline for choosing an appropriate RDF database system and applying a No SQL database in storing and querying RDF data. However, for a larger data set, MongoDB performs well for queries with simple operators while My SQL offers an efficient solution for complex queries. Based on the experimental results analysis, our proposed system outperforms other database systems for most queries when the data set size is small. We compare three database systems, which are Apache Jena TDB (native RDF store, My SQL (relational database, and our proposed system with MongoDB (No SQL database. We evaluate the proposed design and implementation by using the Berlin SPARQL Benchmark, which is one of the most widely accepted benchmarks for comparing the performance of RDF storage systems. We choose MongoDB to represent a No SQL database because it is one of the most popular high-performance No SQL databases. In this paper, we propose a method to exploit a No SQL database, specifically MongoDB, to store and query RDF data.
Resource Description Framework (RDF is a standard for describing web resources.
This causes the need for Semantic Web technology to quickly analyze such big data. Its metadata is widely used in order to fully exploit web information resources. Design and evaluation of a No SQL database for storing and querying RDF dataĭirectory of Open Access Journals (Sweden)įull Text Available Currently the amount of web data has increased excessively.
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