Choosing the right database management system (DBMS) for your company is a big choice, representing a strategic opportunity to significantly enhance IT operations. Make the...
Choosing the right database management system (DBMS) for your company is a big choice, representing a strategic opportunity to significantly enhance IT operations.
Make the right decision and you’ll be able to efficiently manage, analyze, and retrieve company data for years to come.
A wrong choice, on the other hand, could lead to poor performance, scalability issues, higher maintenance costs, and limited functionality that hampers business growth.
Unfortunately, the DBMS landscape is confusing. There are so many solutions out there.
Fortunately, we’ve narrowed down the field and reviewed the two most effective forms of DBMS.
Today, you’ll learn the strengths and weaknesses of relational and NoSQL database systems, plus seven key considerations to keep in mind during the evaluation process.
Selecting the right DBMS provides key benefits to your business:
Below we’ll compare the two most common DBMSes — relational and NoSQL systems — so you can figure out which is best for your specific business.
Who should use it: Companies with well-defined, stable data structures and teams that need to manage complex SQL queries, data relationships, and transactions.
A relational database management system is a type of system that organizes data into tables with rows and columns, where relationships can be established between different tables using common fields.
Common examples of RDBMSes include:
RDBMS is the oldest and most widely used system for managing databases. It’s known for its unmatched stability and reliability.
In the tech world, old doesn’t usually have the best connotation, but with database systems it’s a strength. Over the years, through deployment in a variety of companies of all sizes, these systems have only improved through iteration.
Plus, since RDBMS technologies are so popular, there are countless database management applications that work well with this type of system — for example, IDERA’s database management platform. There’s also a lot of online support, training, and documentation that’ll help you and your team get the most out of your chosen technology.
In terms of data integrity, these systems are hard to beat. In compliance with ACID properties, RDBMSes ensure that your database remains consistent before and after each data transaction.
https://www.geeksforgeeks.org/acid-properties-in-dbms/
Lastly, relational systems are ideal for making complex queries, especially using SQL.
For example, let’s say a financial analyst was calculating the average transaction amounts for premium customers who made purchases in multiple categories over the last 2 years.
This query involves multiple table relationships and complex aggregations that RDBMS handles efficiently through its optimized query engine and indexing.
SQL-based RDBMSes require a rigidly defined schema, so if your company has unstructured data (or structures that are likely to change) it may not be for you.
Despite having open-source options like MySQL, these systems can become quite expensive. That’s the price you pay for the data integrity, security, and stability.
Conventional RDBMS might also struggle to provide the dynamic environment required for AI and machine learning workloads, as Founder Dhanvin Sriram discovered:
“Traditional relational databases can struggle with real-time data processing, so we moved to a hybrid setup, using PostgreSQL for structured data and a vector database like Pinecone for AI-related tasks.” — https://luppa.ai/
Who should use it: If you have loosely-defined data structures, structures you expect to change in the future, or machine learning workloads, a NoSQL system is likely the right choice.
NoSQL (Not Only SQL) databases are the most popular non-relational database system.
They’re designed for flexible data models, horizontal scalability, and handling massive volumes of relatively unstructured data, such as:
Unlike RDBMS, they don’t require fixed schemas. They also do not store data in a tabular format (fields, rows, and columns). Instead, NoSQL systems use one of four data models: document, key-value, graph, and wide-column databases.
Examples of NoSQL database management systems include:
NoSQL databases excel in situations requiring rapid scaling, high performance with big data, and schema flexibility, making them ideal for applications like social media, customer feedback analysis, real-time analytics, and content management systems.
Take the example of a business that needs to track user clicks, page views, and interactions on an e-commerce site during a flash sale.
NoSQL’s ability to handle high-velocity, unstructured data makes it more efficient than RDBMS for this type of analysis.
Despite possessing the ability to handle a wide variety of data types, NoSQL systems lack the query flexibility you’d find in a conventional RDBMS.
Their data models (document, key-value, graph) don’t support JOIN operations like RDBMS. And without structured relationships between data, complex queries become difficult to execute efficiently.
Further, NoSQL technologies often sacrifice ACID-compliance for processing speed. So, even if it can perform complex transactional queries, they’re just less reliable.
Another potential issue is that since NoSQL systems are newer, it may be difficult to find answers to your troubleshooting questions.
On Hybrid Systems: Some companies create IT architectures that include both RDBMS and NoSQL systems, using the former for sensitive transactions and the latter for high-volume, dynamic content.
Below are six factors to consider when evaluating various DBMSes, from relational systems like Oracle and MySQL to NoSQL platforms like MongoDB.
Before you decide between relational and NoSQL, you need to reflect on your business’s current and future data handling requirements.
Ask yourself the following questions:
This step is essential.
Barbara Robinson, Business Intelligence Manager at WeatherSolves Structures Inc, can attest. Her company made the mistake of prioritizing new flashy features over their company needs:
“Early on at WeatherSolve, we chose a system based on features rather than real-world needs, and it became a headache fast. Scaling was an issue within two years, and queries that once ran smoothly started dragging down performance.”
Consider your most ambitious growth plans.
Now choose a DBMS that will grow with you and be able to handle the increases in data volume and the associated challenges this brings to your specific organization. Otherwise, you’ll have headaches down the line during a database system overhaul.
Sometimes, it can seem like a NoSQL system is right for you in terms of scalability, since it’s known for handling large amounts of data. But don’t fall for this assumption.
To illustrate why, let’s look at a scenario. Imagine a hospital is expecting rapid patient growth over the next five years and they need a new database management system.
Which should they choose?
Probably a relational system.
At first glance, you might think, “but isn’t NoSQL better for huge data volumes?” Well, if processing speed is what they’re after, then that would’ve been the smart choice.
But hospitals don’t need speed. They need accuracy — patient records require strict data integrity. Otherwise someone with a penicillin allergy might get a penicillin shot.
In short, they chose to manage data growth through vertical scaling (more powerful servers) rather than NoSQL’s horizontal scaling, since data consistency was more critical than raw performance.
According to the state of data ops report, IT professionals think strong data security is the most critical attribute of data operations technologies.
https://boomi.com/wp-content/uploads/Report-ESG-State-of-Data-Ops.pdf
Features to look for include user authentication, data encryption, access controls, vulnerability scanning, and data masking.
In general, relational database systems are considered more secure than NoSQL systems, because they tend to offer more advanced in-platform security features.
They also typically integrate well with database software tools that can bolster security, like ones that offer AI-driven threat detection.
For example, Idera SQL Secure can automatically identify security violations and ensure your security policies are enforced.
Your DBMS should seamlessly integrate into your current IT infrastructure — the systems, processes, and third-party applications you use to manage and manipulate data.
A well-integrated DBMS ensures smooth data exchange between different applications (e.g., CRM, ERP, BI tools), reducing manual work and data silos.
Since most modern businesses rely on multiple software solutions, it helps if your DBMS supports relevant APIs, connectors, and standard protocols (like SQL, REST, or GraphQL) to connect with these platforms.
In terms of integrations, relational, SQL-based systems are usually better for enterprise brands since they are easy to integrate with a variety of popular tools.
A variety of professionals, ranging in technical skill, will likely be using your database management system and its associated applications.
In fact, in a recent survey of IT professionals found that 84% of organizations report an increase in the number of end-users who have access to data and analytics.
Therefore, ease-of-use should be top of mind.
The more intuitive the user interface, and the more documented and simple the querying language, the less money you’ll have to spend on training and hiring staff.
MySQL, an open-source relational DBMS, has one of the lowest learning curves. Plus, thanks to its widespread use, there are numerous online tutorials and forums dedicated to supporting users.
On the other hand, a more advanced DBMS, like Oracle, often requires specialized training.
In fact, according to Rob Stevenson, Founder of BackupVault, a lot of companies underestimate the complexity of some of these tools.
“Many businesses choose a powerful database without thinking about who will run it. If you don’t have an in-house database administrator, a fully managed solution like AWS RDS or Google Cloud SQL can save you a lot of headaches.”
In sum, consider the technical knowledge of your admins, as well your budget for training them, before committing to a DBMS.
Pro Tip: Look for database technologies with automation features like AI agents that can accomplish repetitive data management tasks for your team.
Legal compliance should never be an afterthought when it comes to data management.
Make sure that your database management system makes it simple to comply with relevant regulations. Otherwise, you may face fines and penalties.
Vivek Vaidya, CTO of Ketch, has spent years building scalable, secure data systems while ensuring privacy law compliance.
He’s “seen companies scramble to add security and compliance features after their database is live, and it’s always a mess.”
This factor is worth even more mulling over if you handle sensitive or private customer data.
If your business deals with customer data, use a database system that makes encryption, access controls, and GDPR/CCPA compliance easy from the start.
Vivek recommends looking for built-in compliance tools:
“At Ketch, we learned that databases with built-in auditing and fine-grained permissions, like PostgreSQL or MongoDB, save time and headaches later.”
Buying a DBMS solution is like buying a house.
There are numerous cost factors to consider, other than the initial and recurring payments.
When selecting a DBMS, you need to factor in not only upfront implementation costs and recurring platform fees, but also indirect costs like ongoing maintenance, staff training, and scalability costs.
These can all jumpscare you like a ghost in your new home’s attic if you don’t estimate them in advance and choose a system that will work with your budget as your operations expand.
Commercial DBMS solutions like Oracle typically have high upfront and recurring costs.
On the other hand, open-source alternatives like MySQL may cost less, but require more in-house expertise. And that means paying top dollar for seasoned SQL administrators and data scientists.
Cloud-based DBMSes typically offer flexible pricing. However, pricing can become expensive with increased data storage and usage.
As you can see, there’s a lot of variability in the market. So run detailed cost analyses on each DBMS and compare them to find the most affordable option for your needs.
In sum, when choosing a DBMS, you’ll typically choose between a relational and NoSQL system:
RDBMS is best for companies that need:
NoSQL is best for companies that need:
After you’ve selected your type, explore the various commercial and open-source solutions for each, and analyze each one across seven criteria: data needs, scalability, security, integrations, ease-of-use, compliance, and cost.
Selecting the right Database Management System (DBMS) is a strategic decision that can shape the efficiency, scalability, and security of your data operations. Whether you opt for a relational database for its robust data integrity and complex query capabilities or a NoSQL system for its flexibility and scalability, the key is aligning the technology with your business’s long-term needs.
A well-chosen DBMS ensures optimal performance, cost efficiency, and seamless integration with existing systems, while also supporting compliance and security requirements. However, managing and optimizing a database doesn’t stop at selection—it requires ongoing monitoring, security enforcement, and performance tuning to maintain operational excellence.
For businesses looking to maximize the efficiency and security of their SQL Server environments, Idera Software offers a suite of industry-leading solutions designed to simplify database monitoring, security management, compliance auditing, and performance tuning.
Ready to optimize your database management strategy? Explore Idera’s SQL Server solutions and take control of your database management and performance today.
Contact our sales team to get a personalized demo of our database management software for SQL Server!
