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Databases are collections of information that is stored in an organized manner and containing minimal to no redundancy (Elmasri & Navathe, 2015). Databases are meant to store as well as manage a large body of information. Management of data entails a collection of other processes among them being; definition of the manner in which the data will be stored and the mechanisms on which the data will be operated. According to Elmasri and Navathe (2015), advanced databases are versions of the relational databases that emerged earlier although the later are able to perform more advanced roles. With the evolution of databases from simple databases to the level of advanced databases, there are benefits that have been associated with them, and also there are demerits that came into play. This research paper will explore the merits and demerits of advanced databases as well as the various features that are associated with different types of databases.

Advanced Databases and Their Functions

While essential databases are relational databases, object-oriented databases, data warehouses, and even the transactional databases, there are only two categories of advanced database systems (Elmasri & Navathe, 2015). The first one is the application-oriented databases that are created with the aim of solving a specific problem. On the other hand, the second category of the advanced database is the object-relational databases which are meant to establish a connection between one object and another in database programming. Most of the advanced databases perform specialized roles and have some several similarities in terms of the manner in which they operate.

Multimedia Databases

In the modern world, multimedia content is on the rise (Kumar & Dwivedu, 2015). There are differentiated sources of multimedia content which involve animations, videos, and even audio contents. Since there is the need to have repositories containing such information, multimedia databases are created for such purposes. Multimedia databases are stores that manage and represent an extensive collection of multimedia data such as graphical data, hypertext data, speech, images, videos, and even audios (Elmasri & Navathe, 2015). To store the data on the multimedia databases, multimedia database management systems are required, and they handle huge amounts of data with different data types.

Since time is passing, there is the need to ensure that essential patterns regarding multimedia content can be extracted. Multimedia databases provide for this option through data mining which allows for classification as well as prediction of future trends through critical analysis of the data extracted (Elmasri & Navathe, 2015). Mining as a generic word is applied although each type of data contained in these databases has an independent type of data mining (Kumar & Dwivedu, 2015). The popularity of these databases is since they are applied in many areas among them being; gaming, video conferencing, process control systems, songs, films, and even libraries among other areas. The figure below indicates how a tiered multimedia database is implemented.

Figure 1: Illustration of how the multimedia databases work (Kumar & Dwivedu, 2015).

Spatial Databases

There are other types of advanced databases that are being applied to the modern world. They collect and store information related to spatial features of the earth especially geographical data (Elmasri & Navathe, 2015). They are so advanced that they store data in raster image format which consist of n-dimensional maps and later projected on the screen as polygons and lines or points. In order for the data stored in the spatial databases to be accessed, spatial database management systems are used. These systems are so crucial that they support indexing and data modeling which are advanced roles performed in the databases (Elmasri & Navathe, 2015). When this data is stored in the database for an extended period, it becomes crucial to extract useful traits and patterns from it, and this is made possible through spatial data mining. These graphical databases have wide areas of applications which include forest planning and ecosystem protection which are carried out using a centralized or distributed system.

Figure 2: Illustration of how spatial databases work (Kumar & Dwivedu, 2015).

Heterogeneous Databases

According to Elmasri and Navathe (2015), these are more advanced databases that are set up to create an interrelation between database modules. The purpose of this communication is to ensure that information is swapped while queries are also being answered. It is important to note that it is possible to have objects in one module differing from objects in another module of the same database (Elmasri & Navathe, 2015). This implies that with heterogeneous databases, it is possible to store different types of data in a single module but with a relationship. Further, heterogeneous databases combine a set of other advanced databases.

Figure 3: Illustration of how heterogeneous databases work (Kumar & Dwivedu, 2015).

Pros and Cons of Advanced Databases

There are many benefits that are associated with advanced databases. Similarly, there are many disadvantages that are associated with the same.

Pros of Advanced Databases

The first advantage of advanced databases is that they have improved shareability and local autonomy of the information (Thakur, 2017). Due to the fact that data can be shared across a range of users, it has facilitated collaboration among individuals. Although people can collaborate, it is possible to maintain the local autonomy whereby data is stored close to the person working on it. However, a global database administrator ensures that the system is operational and effective (Thakur, 2017).

Secondly, advanced databases have facilitated availability since they do not depend on a single centralized database (Yan & Ma, 2011). In the case of the latter, the failure of the central repository implies that the database is not available for the rest of the users. With these advanced databases, failure of a single node does not mean an overall failure. Instead, it implies that all the other nodes can continue reinforcing the failed node until the problem is rectified.

Thirdly, with the advanced databases, there is better and improved performance (Yan & Ma, 2011). Advanced databases have better performance owing to the fact that one can perform more than one function in the database. Other than storing, manipulating, and accessing the information, it is possible to mine data and determine indirect patterns that are directly visible from the look of the eye (Yan & Ma, 2011).

Cons of Advanced Databases

First, relative to the simple relational databases, advanced databases are complex on nature (Conway, 2017). This implies that understanding them and their functionality might require an advanced level of expertise. The built-in replication of databases and the algorithms on which database modules are implemented raises the level of complexity. This implies that a single module’s failure would lead to effects on the availability of the database, performance, and even reliability of the same.

Secondly, there are huge costs that are associated with advanced databases. The requirement of their implementation over a cloud environment implies that additional hardware, software, and expertise are required (Conway, 2017). These requirements imply that the entity applying it must incur some additional costs. These costs may result in serious financial challenges in an organization considering that they may not have been foreseen (Conway, 2017).

Thirdly, advanced databases face a severe challenge of databases security (Kumar & Dwivedu, 2015). Database security entails protection of information in the database against unauthorized access. Due to the implementation of different standards across different modules, securing advanced databases becomes a daunting task (Kumar & Dwivedu, 2015). Further, with the rising complexity and differing standards on which the databases are implemented, securing these databases remains a serious challenge. Due to the possibility of feeding information and accessing information from different modules, a breach of one module’s security might result in an entire database’s security breach.

In summation, it is evident from the discussion above that advanced databases have changed the status quo. The manner in which operations in the databases were carried out is different from the manner in which they are being carried out. One functionality that is exceptional with the advanced databases is the data mining functionality which it brings with it many benefits with regards to future predictions. Although the advanced databases have many advantages, there are many challenges that they are facing although if proper mechanisms are put in place, better results can be achieved.

References Conway, M. (2017). Learn filemaker pro 16: The comprehensive guide to building custom databases. Lewisburg: Apress. Elmasri, R., & Navathe, S. (2015). Fundamentals of database systems. Miami: Pearson Education. Kumar, K., & Dwivedu, A. (2015). An analysis of different types of advanced databases based on basic factors. International Journal on Recent and Innovation Trends in Computing, 2-6. Thakur, D. (2017, Jul 04). Advantages and disadvantages of advanced distributed database systems. Retrieved from ecomputernotes.com: http://ecomputernotes.com/database-system/adv-database/advantages-and-disadvantages-of-ddbms Yan, L., & Ma, Z. (2011). Advancaed database query systems: Techniques, applications and technologies. New York: IGI global.