Category: 2. Disadvantages

• The pattern for SQL databases is to scale up the data vertically, where capacity can only be enhanced by adding capabilities, such as RAM, CPU, and SSD, on the existing server or by relocating to a larger, more expensive one. As your data expands, you’ll need more hard drive space and quicker equipment to operate developing and more advanced technologies. Your database vendor will most likely require you to upgrade your hardware regularly in order to run their most recent releases.
• Hardware can easily become outdated in this context. Each update will undoubtedly be costly and resource-consuming. SQL’s hardware requirements include continuing, day-to-day maintenance and operational costs.

• Relational databases, which were created at a time when data storage was expensive, try to eliminate data duplication. Each table has unique data that may be linked and queried using common values. However, as SQL databases grow in size, the lookups and joins necessary between multiple tables can cause performance issues, ultimately slowing down things.
  

• The schema of a SQL database must be specified before it can be used. They are rigid once installed, and changes are often complex and time-consuming. As a result, significant work must be invested in upfront preparation before the database is ever put into production.
• They are only useful when all your data is structured, and you don’t expect a considerable volume or data type change.

• Some versions are expensive, which makes programmers unable to access them. For example, SQL Server Standard costs around $1,418 per year.
  

SQL does not provide programmers complete control over databases. This is primarily due to hidden corporate rules.

• SQL databases typically scale up vertically by increasing hardware investment. This is both costly and time-consuming. An organization may seek to scale a SQL database horizontally using partitioning in particular instances.
• This extra complexity increases the time and resources required. The effort will certainly require coding for dealing with a large database, which will require highly talented and well-paid developers. Scaling your SQL database as data volume grows is like playing a never-ending game of tag, where the optimum setup is always just out of reach.