Thanks to many technological marvels of our era, we’ve moved from writing important documents using pen and paper to storing them digitally.


Database systems emerged as the amount and complexity of information we need to keep have increased significantly in the last decades. They represent virtual warehouses for storing documents. Database management systems (DBMS) and relational database management systems (RDBMS) were born out of a burning need to easily control, organize, and edit databases.


Both DBMS and RDBMS represent programs for managing databases. But besides the one letter in the acronym, the two terms differ in several important aspects.


Here, we’ll outline the difference between DBMS and RDBMS, help you learn the ins and outs of both, and choose the most appropriate one.


Definition of DBMS (Database Management Systems)


While working for General Electric during the 1960s, Charles W. Bachman recognized the importance of proper document management and found that the solutions available at the time weren’t good enough. He did his research and came up with a database management system, a program that made storing, editing, and retrieving files a breeze. Unknowingly, Bachman revolutionized the industry and offered the world a convenient database management solution with amazing properties.


Key Features


Over the years, DBMSs have become powerful beasts that allow you to enhance performance and efficiency, save time, and handle huge amounts of data with ease.


One of the key features of DBMSs is that they store information as files in one of two forms: hierarchical or navigational. When managing data, users can use one of several manipulation functions the systems offer:


  • Inserting data
  • Deleting data
  • Updating data

DBMSs are simple structures ideal for smaller companies that don’t deal with huge amounts of data. Only a single user can handle information, which can be a deal-breaker for larger entities.


Although fairly simple, DBMSs bring a lot to the table. They allow you to access, edit, and share data in the blink of an eye. Moreover, DBMSs let you unify your team and have accurate and reliable information on the record, ensuring nobody is left out. They also help you stay compliant with different security and privacy regulations and lower the risk of violations. Finally, having an efficient database management system leads to wiser decision-making that can ultimately save you a lot of time and money.


Examples of Popular DBMS Software


When DBMSs were just becoming a thing, you had software like Clipper and FoxPro. Today, the most popular (and simplest) examples of DBMS software are XML, Windows Registry, and file systems.



Definition of RDBMS (Relational Database Management Systems)


Not long after DBMS came into being, people recognized the need to keep data in the form of tables. They figured storing info in rows (tuples) and columns (attributes) allows a clearer view and easier navigation and information retrieval. This idea led to the birth of relational database management systems (RDBMS) in the 1970s.


Key Features


As mentioned, the only way RDBMSs store information is in the form of tables. Many love this feature because it makes organizing and classifying data according to different criteria a piece of cake. Many companies that use RDBMSs utilize multiple tables to store their data, and sometimes, the information in them can overlap. Fortunately, RDBMSs allow relating data from various tables to one another (hence the name). Thanks to this, you’ll have no trouble adding the necessary info in the right tables and moving it around as necessary.


Since you can relate different pieces of information from your tables to each other, you can achieve normalization. However, normalization isn’t the process of making your table normal. It’s a way of organizing information to remove redundancy and enhance data integrity.


In this technological day and age, we see data growing exponentially. If you’re working with RDBMSs, there’s no need to be concerned. The systems can handle vast amounts of information and offer exceptional speed and total control. Best of all, multiple users can access RDBMSs at a time and enhance your team’s efficiency, productivity, and collaboration.


Simply put, an RDBMS is a more advanced, powerful, and versatile version of DBMS. It offers speed, plenty of convenient features, and ease of use.


Examples of Popular RDBMS Software


As more and more companies recognize the advantages of using RDBMS, the availability of software grows by the day. Those who have tried several options agree that Oracle and MySQL are among the best choices.


Key Differences Between DBMS and RDBMS


Now that you’ve learned more about DBMS and RDBMS, you probably have an idea of the most significant differences between them. Here, we’ll summarize the key DBMS vs. RDBMS differences.


Data Storage and Organization


The first DBMS and RDBMS difference we’ll analyze is the way in which the systems store and organize information. With DBMS, data is stored and organized as files. This system uses either a hierarchical or navigational form to arrange the information. With DBMS, you can access only one element at a time, which can lead to slower processing.


On the other hand, RDBMS uses tables to store and display information. The data featured in several tables can be related to each other for ease of use and better organization. If you want to access multiple elements at the same time, you can; there are no constraints regarding this, as opposed to DBMS.


Data Integrity and Consistency


When discussing data integrity and consistency, it’s necessary to explain the concept of constraints in DBMS and RDBMS. Constraints are sets of “criteria” applied to data and/or operations within a system. When constraints are in place, only specific types of information can be displayed, and only specific operations can be completed. Sounds restricting, doesn’t it? The entire idea behind constraints is to enhance the integrity, consistency, and correctness of data displayed within a database.


DBMS lacks constraints. Hence, there’s no guarantee the data within this system is consistent or correct. Since there are no constraints, the risk of errors is higher.


RDBMS have constraints, resulting in the reliability and integrity of the data. Plus, normalization (removing redundancies) is another option that contributes to data integrity in RDBMS. Unfortunately, normalization can’t be achieved in DBMS.


Query Language and Data Manipulation


DBMS uses multiple query languages to manipulate data. However, none of these languages offer the speed and convenience present in RDBMS.


RDBMS manipulates data with structured query language (SQL). This language lets you retrieve, create, insert, or drop data within your relational database without difficulty.


Scalability and Performance


If you have a small company and/or don’t need to deal with vast amounts of data, a DBMS can be the way to go. But keep in mind that a DBMS can only be accessed by one person at a time. Plus, there’s no option to access more than one element at once.


With RDBMSs, scalability and performance are moved to a new level. An RDBMS can handle large amounts of information in a jiff. It also supports multiple users and allows you to access several elements simultaneously, thus enhancing your efficiency. This makes RDBMSs excellent for larger companies that work with large quantities of data.


Security and Access Control


Last but not least, an important difference between DBMS and RDBMS lies in security and access control. DBMSs have basic security features. Therefore, there’s a higher chance of breaches and data theft.


RDBMSs have various security measures in place that keep your data safe at all times.


Choosing the Right Database Management System


The first criterion that will help you make the right call is your project’s size and complexity. Small projects with relatively simple data are ideal for DBMSs. But if you’re tackling a lot of complex data, RDBMSs are the logical option.


Next, consider your budget and resources. Since they’re simpler, DBMSs are more affordable, in both aspects. RDBMSs are more complex, so naturally, the price of software is higher.


Finally, the factor that affects what option is the best for you is the desired functionality. What do you want from the program? Is it robust features or a simple environment with a few basic options? Your answer will guide you in the right direction.


Pros and Cons of DBMS and RDBMS


DBMS


Pros:


  • Doesn’t involve complex query processing
  • Cost-effective solution
  • Ideal for processing small data
  • Easy data handling via basic SQL queries

Cons:


  • Doesn’t allow accessing multiple elements at once
  • No way to relate data
  • Doesn’t inherently support normalization
  • Higher risk of security breaches
  • Single-user system

RDBMS


Pros:


  • Advanced, robust, and well-organized
  • Ideal for large quantities of information
  • Data from multiple tables can be related
  • Multi-user system
  • Supports normalization

Cons:


  • More expensive
  • Complex for some people

Examples of Use Cases


DBMS


DBMS is used in many sectors where more basic storing and management of data is required, be it sales and marketing, education, banking, or online shopping. For instance, universities use DBMS to store student-related data, such as registration details, fees paid, attendance, exam results, etc. Libraries use it to manage the records of thousands of books.


RDBMS


RDBMS is used in many industries today, especially those continuously requiring processing and storing large volumes of data. For instance, Airline companies utilize RDBMS for passenger and flight-related information and schedules. Human Resource departments use RDBMS to store and manage information related to employees and their payroll statistics. Manufacturers around the globe use RDBMS for operational data, inventory management and supply chain information.


Choose the Best Solution


An RDBM is a more advanced and powerful younger sibling of a DBMS. While the former offers more features, convenience, and the freedom to manipulate data as you please, it isn’t always the right solution. When deciding which road to take, prioritize your needs.

Related posts

Wired: Think Twice Before Creating That ChatGPT Action Figure
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 12, 2025 6 min read

Source:

  • Wired, published on May 01st, 2025

People are using ChatGPT’s new image generator to take part in viral social media trends. But using it also puts your privacy at risk—unless you take a few simple steps to protect yourself.

By Kate O’Flaherty

At the start of April, an influx of action figures started appearing on social media sites including LinkedIn and X. Each figure depicted the person who had created it with uncanny accuracy, complete with personalized accessories such as reusable coffee cups, yoga mats, and headphones.

All this is possible because of OpenAI’s new GPT-4o-powered image generator, which supercharges ChatGPT’s ability to edit pictures, render text, and more. OpenAI’s ChatGPT image generator can also create pictures in the style of Japanese animated film company Studio Ghibli—a trend that quickly went viral, too.

The images are fun and easy to make—all you need is a free ChatGPT account and a photo. Yet to create an action figure or Studio Ghibli-style image, you also need to hand over a lot of data to OpenAI, which could be used to train its models.

Hidden Data

The data you are giving away when you use an AI image editor is often hidden. Every time you upload an image to ChatGPT, you’re potentially handing over “an entire bundle of metadata,” says Tom Vazdar, area chair for cybersecurity at Open Institute of Technology. “That includes the EXIF data attached to the image file, such as the time the photo was taken and the GPS coordinates of where it was shot.”

OpenAI also collects data about the device you’re using to access the platform. That means your device type, operating system, browser version, and unique identifiers, says Vazdar. “And because platforms like ChatGPT operate conversationally, there’s also behavioral data, such as what you typed, what kind of images you asked for, how you interacted with the interface and the frequency of those actions.”

It’s not just your face. If you upload a high-resolution photo, you’re giving OpenAI whatever else is in the image, too—the background, other people, things in your room and anything readable such as documents or badges, says Camden Woollven, group head of AI product marketing at risk management firm GRC International Group.

This type of voluntarily provided, consent-backed data is “a gold mine for training generative models,” especially multimodal ones that rely on visual inputs, says Vazdar.

OpenAI denies it is orchestrating viral photo trends as a ploy to collect user data, yet the firm certainly gains an advantage from it. OpenAI doesn’t need to scrape the web for your face if you’re happily uploading it yourself, Vazdar points out. “This trend, whether by design or a convenient opportunity, is providing the company with massive volumes of fresh, high-quality facial data from diverse age groups, ethnicities, and geographies.”

OpenAI says it does not actively seek out personal information to train models—and it doesn’t use public data on the internet to build profiles about people to advertise to them or sell their data, an OpenAI spokesperson tells WIRED. However, under OpenAI’s current privacy policy, images submitted through ChatGPT can be retained and used to improve its models.

Any data, prompts, or requests you share helps teach the algorithm—and personalized information helps fine tune it further, says Jake Moore, global cybersecurity adviser at security outfit ESET, who created his own action figure to demonstrate the privacy risks of the trend on LinkedIn.

Uncanny Likeness

In some markets, your photos are protected by regulation. In the UK and EU, data-protection regulation including the GDPR offer strong protections, including the right to access or delete your data. At the same time, use of biometric data requires explicit consent.

However, photographs become biometric data only when processed through a specific technical means allowing the unique identification of a specific individual, says Melissa Hall, senior associate at law firm MFMac. Processing an image to create a cartoon version of the subject in the original photograph is “unlikely to meet this definition,” she says.

Meanwhile, in the US, privacy protections vary. “California and Illinois are leading with stronger data protection laws, but there is no standard position across all US states,” says Annalisa Checchi, a partner at IP law firm Ionic Legal. And OpenAI’s privacy policy doesn’t contain an explicit carve-out for likeness or biometric data, which “creates a grey area for stylized facial uploads,” Checchi says.

The risks include your image or likeness being retained, potentially used to train future models, or combined with other data for profiling, says Checchi. “While these platforms often prioritize safety, the long-term use of your likeness is still poorly understood—and hard to retract once uploaded.”

OpenAI says its users’ privacy and security is a top priority. The firm wants its AI models to learn about the world, not private individuals, and it actively minimizes the collection of personal information, an OpenAI spokesperson tells WIRED.

Meanwhile, users have control over how their data is used, with self-service tools to access, export, or delete personal information. You can also opt out of having content used to improve models, according to OpenAI.

ChatGPT Free, Plus, and Pro users can control whether they contribute to future model improvements in their data controls settings. OpenAI does not train on ChatGPT Team, Enterprise, and Edu customer data⁠ by default, according to the company.

Read the full article below:

Read the article
LADBible and Yahoo News: Viral AI trend could present huge privacy concerns, says expert
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 12, 2025 4 min read

Source:


You’ve probably seen them all over Instagram

By James Moorhouse

Experts have warned against participating in a viral social media trend which sees people use ChatGPT to create an action figure version of themselves.

If you’ve spent any time whatsoever doomscrolling on Instagram or TikTok or dare I say it, LinkedIn recently, you’ll be all too aware of the viral trend.

Obviously, there’s nothing more entertaining and frivolous than seeing AI generated versions of your co-workers and their cute little laptops and piña coladas, but it turns out that it might not be the best idea to take part.

There may well be some benefits to artificial intelligence but often it can produce some pretty disturbing results. Earlier this year, a lad from Norway sued ChatGPT after it falsely claimed he had been convicted of killing two of his kids.

Unfortunately, if you don’t like AI, then you’re going to have to accept that it’s going to become a regular part of our lives. You only need to look at WhatsApp or Facebook messenger to realise that. But it’s always worth saying please and thank you to ChatGPT just in case society does collapse and the AI robots take over, in the hope that they treat you mercifully. Although it might cost them a little more electricity.

Anyway, in case you’re thinking of getting involved in this latest AI trend and sharing your face and your favourite hobbies with a high tech robot, maybe don’t. You don’t want to end up starring in your own Netflix series, à la Black Mirror.

Tom Vazdar, area chair for cybersecurity at Open Institute of Technology, spoke with Wired about some of the dangers of sharing personal details about yourself with AI.

Every time you upload an image to ChatGPT, you’re potentially handing over ‘an entire bundle of metadata’ he revealed.

Vazdar added: “That includes the EXIF data attached to the image file, such as the time the photo was taken and the GPS coordinates of where it was shot.

“Because platforms like ChatGPT operate conversationally, there’s also behavioural data, such as what you typed, what kind of images you asked for, how you interacted with the interface and the frequency of those actions.”

Essentially, if you upload a photo of your face, you’re not just giving AI access to your face, but also the whatever is in the background, such as the location or other people that might feature.

Vazdar concluded: “This trend, whether by design or a convenient opportunity, is providing the company with massive volumes of fresh, high-quality facial data from diverse age groups, ethnicities, and geographies.”

While we’re at it, maybe stop using ChatGPT for your university essays and general basic questions you can find the answer to on Google as well. The last thing you need is AI knowing you don’t know how to do something basic if it does takeover the world.

Read the full article below:

Read the article