Speed is a very important factor in websites and other types of applications and almost all applications stores some type of data, normally in a database. For an example a blog typically saves users, posts and comments. There’s a high risk that as the amount of data in the database grows, the time for inserting and requesting specific data increases. If it takes more than some seconds to view a specific page, a user will normally leave the site. However, it’s a fact that the database will grow while the application will become more popular but it’s possible to save a lot of time if using right database, and structure. In this thesis MongoDB and MySQL will be compared with focus on time consumption. SQL (Structured Query Language) is the language which most databases use. This kind of database stores data in structured tables and noting can be added to them if the type of data is incorrect. SQL also support relations between tables. MySQL is a very popular relational database management system (RDBMS) which for example websites frequently makes use of. NoSQL is a new type of databases where the data is stored in collections without any kind of structure, unlike the well known SQL databases where the data is stored in structured tables. Because of the non-structure, these types of databases are designed to be fast and scalable over multiple machines. Mongodb is a such kind of NoSql-database. Tests has been done both on inserting and processing when handling up to 4 millions entities, MongoDB performs better in almost every test. Results shows that the processing time is shorter using MongoDb in the cases that this thesis is covering, and that it’s possible to implement a much fast application when using MongoDb instead of Mysql as database.