The project in five facts.
Challenge, approach and results.
In recent times, an extraordinary growth and development of databases has been observed, which are becoming key building blocks in processing large volumes of data, known as big data. Big data not only contains enormous amounts of information, but often also includes diverse types of data, such as text, images, sound, video recordings and numerous other formats. On the other hand, PostgreSQL is a classic relational database that has proven itself as a reliable solution for complex data analyses through its adaptability and the power of the SQL language. Its integration with the transaction management system (ACID) enables consistency and reliability in critical environments.
Problem
In recent times, an extraordinary growth and development of databases has been observed, which are becoming key building blocks in processing large volumes of data, known as big data.
Solution and Method
Big data not only contains enormous amounts of information, but often also includes diverse types of data, such as text, images, sound, video recordings and numerous other formats. Due to this diversity and scale, it is crucial to have appropriate databases that enable efficient storage, management and analysis of this data. MongoDB and PostgreSQL are among the leading databases used to address big data challenges, each with its own unique characteristics, advantages and limitations.
This diploma thesis focuses on a comparative analysis of the MongoDB and PostgreSQL databases, and their performance and efficiency in processing and analysing big data. MongoDB, as a representative of non-relational databases, proves to be a very useful tool in the big data ecosystem. The ability to store unstructured data and easy horizontal scaling place MongoDB among the popular choices of organisations dealing with diverse and rapidly growing data.
Results
On the other hand, PostgreSQL is a classic relational database that has proven itself as a reliable solution for complex data analyses through its adaptability and the power of the SQL language. Its integration with the transaction management system (ACID) enables consistency and reliability in critical environments. Within the framework of this research, four key measurements will be carried out.
The first measurement will provide results on the speed of document insertion and queries per second. The second will focus on the speed of data insertion into both databases. This measurement will determine their capacity in handling larger volumes of data.
The third measurement will focus on the efficiency of transactional insertion with emphasis on ensuring data consistency and integrity. The fourth and final measurement will examine the scope and scalability as well as memory consumption during database insertion. Through our research, we wish to clearly present where the strengths, limitations and advantages of MongoDB and PostgreSQL lie in processing and analysing big data.
The aim is to gain insight into their capabilities, limitations and how they perform in different data processing scenarios.
Module, programme and stories.
Your diploma project for a real company.
A diploma thesis at Academia solves a challenge from a company – often the one where you do your 800 hours of placement. Read about the Programsko inženirstvo module or book a consultation.