When Software Slows Down as Data Grows

One problem that can occur in software is that a program may perform well at the beginning, but gradually become slower as the amount of data increases, eventually making it difficult or even impossible for users to work with.

One of my experiences in this area involved a large manufacturing company with several branches across the country.

One day, they contacted me and explained that their network-based software had become extremely slow and that users could no longer work with it comfortably. They asked me to investigate whether the problem could be fixed or whether the software needed to be rewritten from scratch.

I initially asked them to discuss the issue with the software's support team.

They explained that the programmer who had developed the software was a former employee who had left the company after retirement and was no longer available.

Given the circumstances, I asked them to provide the software's source code and the necessary access so I could investigate the cause of the problem.

After reviewing the source code, I came across several interesting points.

The source code was relatively small, and the software had been developed using relatively modern technologies. Therefore, at first glance, the problem did not appear to be caused by outdated technology.

However, a more detailed investigation revealed the main cause of the slowdown.

A large number of queries were being executed against the database throughout different parts of the software, and in some areas, proper principles of database query design and execution, as well as application logic, had not been followed.

The result of this design was not particularly noticeable when the amount of data was small. With only a limited number of records, the software performed reasonably well, and users did not experience any significant problems.

But over time, as the amount of data increased, the situation changed completely. Once the data volume reached several hundred thousand records, some operations became extremely time-consuming, and the software was practically unusable for the users.

It became clear that the main problem was not simply the amount of data. The software had not been designed from the beginning to maintain acceptable performance as the volume of information grew.

When Problems Reveal Themselves Over Time

One interesting aspect of this experience was that the software probably appeared completely suitable when the project first started. When there is only a small amount of data in a system, many design and optimization problems may not be visible at all.

But as the amount of data and the number of users increase, technical weaknesses that were not noticeable at first gradually reveal themselves. Even using modern technologies does not, by itself, guarantee good performance. Poorly designed algorithms, inefficient queries, and failure to follow optimization principles can eventually lead to a decline in system performance.

The Lesson This Experience Taught Me

This experience reminded me of an important principle in software design: software should not be designed only for today's conditions; future growth in data and the number of users should also be considered as much as possible.

A software system may be extremely fast with a few thousand records, but the same system can perform very differently with several hundred thousand or several million records.

Therefore, when designing a system, we should not ask only, “Does the software work correctly today?” We should also ask:

“If the amount of data and the number of users increase several times, will this software still be able to maintain acceptable performance?”

Data growth is usually gradual, which is why problems caused by poor design can remain hidden for a long time.

Good software is not simply software that is fast with a small amount of data; it should also be prepared for business growth and increasing data volume.