Database Theory: A Comprehensive Overview - Report Sample

Introduction

Database theory entails a wide variety of subjects that have a connection to the science and research of the realms of theories of the database as well as Database Management Systems (DBMS) (Hansson 2012). The theoretical dimension of database management involves several other aspects such as the foundation of query languages, the explicit power of queries, database design approach, the theory of dependency, the finite model approach, computational complexity, database recovery and concurrence control, spatial and temporal databases, management of uncertainty of data, probabilistic databases and web data (Hansson 2012). A majority of studies done have conservatively been grounded on the relational approach because it is typically considered the most straightforward and most fundamental approach of interest. Similar results for other data approaches include semi-designed models, also referred to as the object-centric dimension (Hansson 2012). The most recent version of database management being the graph data approach which is primarily derived from the relational model. The foundation of database theory is on the relational model, the query, and query language approaches (Hansson 2012).

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The primary concentration of database theory is based on the comprehension of the complex nature and how powerful query languages are and their interconnection to logic. Beginning from the relational algebra, calculus and the first-order logic all which sum up the Codd’s theory allows a person to understand more about the database theory (Hansson 2012). Codd’s approach is linked to the insight that crucial queries, such as the reachability of graphs, cannot be expressed in this language as a more persuasive language founded on fixpoint and logic programming (Hansson 2012). For instance, datalog is studied and used. A second concentration about the subject was on the grounds of the organization of queries and data integration. In this instance, most of the work researched query conjunction that accepts the optimization of queries even under certain constraints using chase calculation.

The Relational Model

During the old days of databanks, it emerged that the storage systems were insufficient answers for keeping vast quantities of information. For these reasons, there was a proposal to develop more database models to include a hierarchical approach and the network approach. While this was going on, an instrumental idea during that period was that questioning a database was not dependent on how and where the information was preserved (Mayfield et al., 2010). The idea is what was termed as the principle of data independence. It is apparent that things were not easy, and the trial kept coming up. Among the most significant discoveries in the field of computer sciences was the Codd relational theorem of 1970 (Mayfield et al., 2010). The theory is one of the dominating ones in the database sectors. Additionally, considerable results have been based on the relational theory.

In short, the fundamental concept of relational theory on databases is to preserve data in forms of tables and a more mathematical viewpoint (Mayfield et al., 2010). In this model, the ideal data is provided by a set of columns of tabulation and the relation tuples. Thus, each tuple contains a single entry for each value. Generally, it is presumed that individual entries result from fixed infinite variables of ideal database aspects.

The Query Model

Ideally, the primary role of preserving information in databases is to be able to refer to it for the query. For instance, one might have an interest in understanding all the written operas. The aftermath of this kind of query is interested party interrogating and acquiring the information intended for whatever reason. In a more precise version, in the relational databases, terminologies contain the relationship with the tuples and columns in a table. Some subtitles in a database connection with the terminology, computable query whose explanation will follow in the later paragraphs (Jha & Suciu, 2013). First, the idea of computation is defined to function as mapping points to points. Therefore, a complication may result from the concepts that the tuples in a relational approach are not ordered. The lack of this ordering is where the connection between tables and relations becomes a failure. In this case, when a relation is represented by a table, the rows must be put into a similar order. The approach is nonetheless regarded a repair for individual connections; thus, the entire column transposition in a tabulation represents a similar relation (Jha & Suciu, 2013).

Query Languages

There is an ultimate requirement for query languages to permit the database access to form their own simplified questions without allowing any specialized knowledge in the database technicalities apart from the general knowledge of the database schema (Jha & Suciu, 2013). Query language enables the database user to place semantically simple questions at any time. It is imminent to mention that a person needs to keep off using a programming language for interrogating databases for reasons such as not all can understand the language. These languages are also prone to errors and not appropriate for the optimization of queries (Jha & Suciu, 2013). Notably, the users do not require being specific on how the query is produced but only concerned about the qualities of the expected results.

Expressive Power

Expressive power is used in the query language, which is a collection of questions that can be expressed at a time. It is, therefore, a critical model for comparison of various query languages. An example is the expressive power is able to explain if certain traits such as redundancy (Mayfield et al., 2010). Comprehensive knowledge about the expressive power of query language is a hard assignment. Demonstrating that a question cannot be expressed leads to a lower bound proving, which is hard to obtain. However, the close connection of relational query language with algorithm logic permits the application of approaches from the area to have an insight into the abilities and weakness of the query language theory.

Data Complexity

Complex data is examined from time to time and can be optimized to facilitate a smooth analysis. Additionally, queries that are analyzed once on massive databases also require optimization (Mayfield et al., 2010). To optimize a query, the cost approach is applied to determine what optimizers can do. There are a variety of methods to use to compile a query into an examination plan. Moreover, there are many methods of illustrating a question into an appropriate query language needed in a specific time (Mayfield et al., 2010). Its thus relates to various similar query characterization, which may introduce fundamental evaluation techniques after a successful compilation.

Real-life DBMS examples include a bank database connected to different entities about the customers like account numbers and types, transaction tables, and other details under protection. Another example is a hospital database that involves protected information about patients' conditions, treatment, and other procedures.

Conclusion

Database theories have been formulated to safely provide answers about how data can be stored, retrieved, and processed. Among the most critical theory is the relational theory, which is fundamental. Database theories also have various other general notions such as queries, query language, expressive power, and data complexity as they all attempt to explain databases and how they work.

References

Hansson, S. O. (2012). A textbook of belief dynamics: Theory change and database updating.

Springer. Jha, A., & Suciu, D. (2013). Knowledge compilation meets database theory: compiling queries to decision diagrams. Theory of Computing Systems, 52(3), 403-440.

Mayfield, C., Neville, J., & Prabhakar, S. (2010). ERACER: a database approach for statistical inference and data cleaning. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of data (pp. 75-86).