In addition to the traditional approaches using relational databases, new so-called big data technologies have been established for analytical applications in recent years. These technologies differentiate between whether the data is analyzed before it is saved to persistent storage ( data in motion ) or whether it is only examined after it has been stored ( data at rest ).
The former is used when the data volume needs to be condensed before storage for capacity reasons, or when it is necessary to have benin telegram screening the results of the data analysis immediately after it is generated and it is not possible to save the data beforehand for response time reasons. In the following, however, the focus will be on technologies for data at rest . With these big data technologies, a distributed approach is usually chosen for scalability reasons, and the storage and processing of semi-structured or unstructured data is usually better supported by BLOBs ( Binary Large Objects ) than with traditional relational systems .
This naturally raises the question of whether programs, data and methods from the relational world can also be used for and with the big data world. This article will examine this.