Database automation tools offer a variety of purpose-built automation capabilities that apply to the DBMS and the associated infrastructure operations tasks.
Discussion 1: Lia Chmielinski
Database automation helps make complex and time consuming tasks simple and fast. They are best used for tasks that are time consuming and repetitive that consume productivity. Virtual automation avoids dull, exhausting work. Automation tools free up the DBAs time to focus on patching, scaling, provision, and other tasks and they don’t have to manually check and update the code.
The automation tool we used in class MS SQL Server is capable of handling large amounts of data and versatile features and is used for performing unit testing. Some examples of things we can automate include: provisions of servers, deployment of a new database cluster, import of existing database cluster, automatic node, automatic switch over, backup and restore, generate reports like graphs, generate query analysis, and processing query logs to name a few. These tasks are useful to be automated so that they have less errors and are done quickly.
A relational database system is the most popular, successful and widely used database system. RDMS is the most useful database automation tool overall because it has had a lot of time to mature and is a standard for saving and querying data. The tabular presentation is in RDMS trouble free and uncomplicated for database end users to use and identify with. The different queries of a database help to search any column within in a given condition or matching criteria. Most developers are experienced in relational data modeling. It is also the most successful, where “in 1999, the sales revenue of $11.1 billion for relational and object-relational databases, but only $211 million for OO databases” (2020, Debnath). Object Operational databases don’t compare to high transaction volumes and user counts necessary for business purposes as well as relational databases. RMS can handle traditional business data processing applications that require high performance, reliability, and scalability. Businesses have invested so much money and resources in the RMS development that change to OO wouldn’t be cost effective or efficient.
Source:
Namuag, P. (2021, April 9). How to get started with Database Automation. Severalnines. Retrieved September 25, 2021, from https://severalnines.com/database-blog/how-get-started-database-automation.
Debnath, M. (2020, February 10). How do OODBMS and ORDBMS differ from RDBMS? Database Journal. Retrieved September 24, 2021, from https://www.databasejournal.com/features/db2/how-d…
Discussion 2: Moses Ebea
Database automation tools offer a variety of purpose-built automation capabilities that apply to the DBMS and the associated infrastructure operations tasks. I have learnt that OODBMS and RDBMS are working supplementary to each other leading to a new concept called the ORDBMS. But soon OODBMS will become the new standard for the database. ODMG can handle complex data and a wider variety of data types, save, and retrieve data quickly, integrate with object-oriented programming languages, easily model advanced real-world problems, and are extensible with custom data types.
An OODBMS combines object-oriented programming paradigm with traditional database management principles. That is, it must inevitably support abstraction, encapsulation, polymorphism, and inheritance and at the same time it should provide means for database management concepts such as the ACID properties (Atomicity, Consistency, Isolation and Durability) which lead to system integrity, support for a query language and secondary storage management systems which in turn allow for managing very large amounts of data.
Deepika et al. (2016) opined that advanced Office Automation Systems OODBMS in such systems handles hypermedia very efficiently as their lays commonalities between database and the hypermedia model. With the direct implementation of many a data structures with utmost ease, OODBMS fits such applications like a glove.
Reference:
Depika, S., Neha, S., Nidhi, J., & Ami, N. (2016). Empirical performance comparison of OODBMS over RDBMS. Comp. Science and Engineering Department, Institute of Technology, Nirma University 7(1), 83-88. doi: 10.090592/IJCSC.2016.012
Discussion3: Sunil Lakhanpal
Database automation means leveraging processes and tools to make admin tasks for a database simpler and safer. By using database automation for your database management, you not only have fewer deployment errors but also higher reliability and speed on changes implementations. Database automation software can protect against any unwanted outcomes. Database automation can help forecast the impact application changes will have on the database. With this information, database administrators can use those forecast reports to quickly discover issues instead of taking days to find them.
Database automation tools offer a variety of purpose-built automation capabilities that apply to the DBMS and the associated infrastructure operations tasks. Data processing tasks includes automation data collection, replication, cleanup, and migration tasks that help make the data more meaningful, secure, dependable, and available for immediate processing when necessary (Duez et. al. 2006).
Though there are variety of database management systems such as RDBMS, ORDBMS and OODBMS. The majority organizations including my organization are using the Relational Databases and Object Relational Databases such as SQL Server, Oracle, PostgreSQL and MySQL that has dominated the market. The flexibility in data reusability which helps in reducing the time and cost of the database designing and working with the complex datatypes are the key advantages that my organization was able to gain using the object relational databases.
My organization also currently utilizing the SQL Server SSIS, SSRS and SSAS tools along with the Cluster Control to automate many of the database procedures and tasks that needs to perform regularly, from deployments, upgrades, discovering and troubleshooting anomalies, recovering from failures, topology changes, running backups and verifying data integrity, scaling and more.
Reference:
Duez, P. P., & Jamieson, G. A. (2006, July). Toward designing for trust in database automation. In Proceedings of the 5th American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Controls, and Human Machine Interface Technology
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