Comparative analysis of efficient methods for storing unstructured data into database with accent on performance

the management of unstructured data is recognized as one of the major unsolved problems in the information technology (IT) industry, the main reason being that the tools and techniques that have proved so successful transforming structured data into business intelligence and actionable information simply don´t work when it comes to unstructured data. This unstructured data is often stored outside the database, separate from its structured data. This separation can cause data management complexities. Or, if the data is associated with structured storage, the file streaming capabilities and performance can be limited. User data is produced and generated on big scale where measurement is hundreds of MB or even couple of GB per user per day. Efficient method for storing and accessing those kinds of data is imperative in modern information society. In this paper we are presenting results of research on using different data types for storing unstructured data within database and classic file system. Research is inspired with current situation in modern information society.