Essential Database Design Tips for a Successful DB Implementation in 2021

Database Design
Database Design

This article discusses why normalization is not enough (unlike the common belief) in terms of database modelling and database design. A well-planned and healthy database can distinguish between your flawless enterprise application with a buggy-filled one. Having a tampered database can cause troublesome brand damage to your enterprise, which may also lead to the need for weeks of remediation and patching. This is why you have to focus on database design, which is often a neglected aspect. In the modern-day enterprise database implementation, it is of paramount importance to design your database as per the standards. Let us explore how.

1.Get the fundamentals right

At the baseline, you have to pay close attention to the planning of your database. However, this is an often-neglected aspect, which may be proven further to be a weak link in the enterprise ecosystem forever. Proper data modelling needs to come before the database development stage. Ignoring the planning phase will lead to a later cumbersome need to restructure, replace, or scrapping the DB.

2.Documenting model

While making a data model for your enterprise DB, it is not enough to name the objects. If you do not document these properly, their meaning may become unclear and non-understandable later. To do this well, you may try the following practices.

  • Use a proper naming convention to be followed in documentation – You should document the definitions of all the columns, tables, and definitions you specify in the DB. This makes it unique across the level, and even the developers can access the information as such.


  • Documentation needs to describe the expectations of database structure sell – This approach will help when the new developers are trying to join the existing projects and follow up with the work done by previous predecessors.

3.Watch the primary keys

The tables in a database design a primary key as an identifier for each row in it. It would help if you first decided which all columns need to be made a part of the primary key and all values you have to include. Each table here needs an identifying key and does not neglect the need for the keys’ required uniqueness. This way, things will be made easier for you to specify and map relations between rows and tables. If you are not sure of doing it the proper way, you may get a database design expert’s assistance.

4.Avoid Nulls

It is found that allowing the nulls in the DB tables may complicate the application programming further as required to access the same. Say, for example, if there is an address record that lets two address lines under the same as Address#1 and Address#2. Further, if the address line has only one address, then the second line is left blank. Even when the second address like value is left blank, it is not the same as null. Even the minor details become very important in such cases. So, it is always advised to avoid nulls in the DB tables.

5.Follow the naming conventions

As we have seen once, naming conventions offer a better insight into all involved about the table models and DB fields. In the design phase itself, pick a proper naming convention relevant to your business to be given to the database objects and then stick it throughout the implementation and maintenance phases. Ensure that this naming convention you follow is logical and gives clear information to the users at all stages. Using such a naming convention, all tables, constraints, columns, and other objects can be consistently and predictably named and used. For any clarifications regarding naming conventions and database design, you can approach expert database services like RemoteDBA.

6.Run integrity checks

Do not underuse overuse integrity checks if the domain tables are good to enforce integrity. These work well while there are many values to check against those or while the checked values tend to change now and then. You can also use third-party apps for integrity checks. However, it is advisable not to use only those as your line of defence. Defining proper integrity rules on DB will also help ensure that these rules are not violated. Using this methodology, data may satisfy defined integrity rules every time. You should not also neglect the need for testing. Try to simulate a real production environment for testing and make testing a crucial part of your data modelling.

What we discussed above are the fundamental steps for a sound DB design. Once you reached this level, use the below tips to optimize your results.


Data normalization is an essential performance tuning approach, which is also a strong mechanism for database integrity. Developers are aware of the problems related to over-normalization. However, often tend to do under-normalization. This may further lead to data replication ending up in insufficient storage and compromised performance.


8.Foreign keys

Experts point out that referential integrity constraints like foreign keys will boost the overall performance. An optimizer can recognize the enforced constraints easily and make better choices for joins and other actions related to data access.

9.Unique constraints

You further boost the performance with the use of unique constraints. An optimizer can ideally use these to enhance the query tuning. All these measures will further enhance the capabilities of your database over time.

10.Archiving old data

Ensure that your database is not holding any outed data, which is not in use anymore. It is best to archive those into the ‘archived’ DB, which can be an OLAP database or kept as a backup file. The larger tables mean complicated table scans and much deeper indexes, with which the locks will be held for significantly longer periods.

11.Separate functions

You may separate all the OLTP production functions’ reporting functions, whereas the OLTP databases tend to have shorter transactions with many updates. The reporting databases as the OLAP and data warehousing systems may have longer and data-heavy queries. You may put those into different servers for more efficient processing.


Taking care of all these needs, many modern automation platforms can help you combat the stability issues, performance bugs, and unplanned downtimes for your database. However, once you have accomplished the design phase well, you will surely cut down a lot of time and chaos in terms of database troubleshooting needs.

Thanks For Reading 
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