Database management systems can assist in sorting information as well as linking databases and reporting changes and trends in database information. Although all database management systems perform the same basic task, which is to allow users to create, edit, and access data in databases, how they do this can vary. Furthermore, the features, functionality and support associated with each management system may vary considerably. Database management engines also need your organization to be able to grow.

Small businesses may need only limited features or have small amounts of data to manage, but requirements can grow significantly over time, and switching to another database management system can be a problem. A very poorly implemented database in the market is IBM DB2. DB2 is a NoSQL-enabled database engine that can read JSON and XML files. It is created by IBM. It is not surprising that it is intended to use on the iSeries servers of IBM, but the version of the workstation works on Windows, Linux, and Unix. The current LUW version of DB2 is 11.1, offering a range of enhancements.

One was a BLU Acceleration improvement designed to make this database engine work faster through data skipping technology. Data skipping is designed to enhance the speed of more data-fitting systems. The latest version also improves the recovery of disasters. Disadvantages of DB2 are:

1. This database is very costly to maintain for small companies.

2. Additional software is required to make clusters

3. Company has to pay for the Database access after that three years free trail to renew license. Designing and managing a database takes more than just installing it – there are many moving parts and pieces, and if they aren’t properly managed, you might end up with a system that is far less efficient than it was meant to be.

Common errors in the design of databases are: Lack of Naming Standards, Improper documentation, Stored procedure overuse, Ignoring Normalization, Maintainability, Encapsulation, Security, Performance, Lack of testing. Primary keys must be system values and unique. They are managed by the DB system so that one can do things like safely moving the data to another system or changing the underlying data without manipulating relationships. When several rows share the data and a shift in one will affect all the other rows, move it to another column. For example, catalog customers should be segregated from their orders.

Data is shared between several columns, but not all other rows should be affected by a shift in one, hold it in one column. Instead, use a data versioning scheme so that the data-related rows will maintain their current values before the switch, and the changed data will enter a new row and the parent row key will be modified. If the data can be changed or used separately from row, placing it in a separate table will make sense logically and provide benefits for data integrity if you are able to lock in rows but not columns. This condition also contributes significantly to the proliferation of stored procedures and primary views, as subsequent programmers strive from the view of their applications to hide the database schema errors. Hard Deletes: When hard data removal makes sense, but in my experience these times are much less frequent than the number of times you’re going to restore the database to a separate server or dig through transaction logs to recover error-deleted data or review an application problem. So, Use soft deletes in database system.