Data retrieval, access, and tuple identification are inevitable in database processing, ensuring performance. The entities and relationships form a relational database. Data themselves are not specifically formatted, requiring sequential data block scanning if the particular index is unavailable. This paper summarizes existing indexing principles focusing on the B+tree, which forms the default structure for data access based on the index key. Such design is reliable and prone to an increase in the amount of data. However, it cannot manage undefined values properly, whereas they cannot be mathematically compared. Secondly, migrated rows can be present due to the size demand extension after the update operation. Thirdly, the index is always balanced, resulting in additional demands of the transaction. All these factors are covered by the proposed paper, discussing the limitations, opportunities, and own solutions to improve the performance. Several architectures are discussed, maintained, and computationally studied, focusing on the size demands, processing time, and costs. By using proposed techniques, significant improvements can be reached. A pointer list is introduced for migrated row management to reference the index set from the data block and store reference path or using a data reflector. When dealing with transaction support, index management and rebalancing are shifted to the separate autonomous transaction. Thanks to that, the main transaction can be approved sooner with no reliability issues. Finally, the proposed paper introduces the NULL value management structure in the instance memory for the index node reference.

Timed data processing is a fundamental requirement for the database systems. It is not, however, only the changes in time management, but also the complex record of changes during the whole life cycle of the object - historical values, actual states, also data valid the future. Existing solutions are inadequate in terms of performance - effectiveness of the whole system. which is manifested using the size of the required data and processing time. This paper deals with the principles of temporal data modeling based on the column level, not the whole object and describes the structure and methods for manipulation. The proposed system is fully temporal and transaction-oriented. This solution is mostly designed for communication systems, intelligent transport system, where the performance based on speed and the size of the transmitted data is needed.