Behind many of the applications you use and data-driven websites you visit, there’s a database management system at work. These cloud-based systems can store your passwords, messages, social media posts (and images), shopping history, and more. Operated by cloud providers and stored in data centers, managed databases back up customer data, maintain security, and ensure scalability, keeping everything organized and accessible for business partners, customers, and the users that interact with them.
The first managed database service provider
In 2009, Amazon launched its Relational Database Service (RDS), the first database service of its kind, and an early example of what is now known as a fully managed database service. Compared to the complex databases we have today, RDS was quite simple—but revolutionary. Using databases like MySQL, it handled routine tasks like backups and security updates, which previously required dedicated database administrators and developers.
Because this fully managed service provider handled all infrastructure maintenance, it freed up technical teams at Amazon to focus on application development rather than having to deal with database management, server monitoring, and maintenance.
How database management systems are used today
Today's database management cloud providers set up data storage, perform regular backups, maintain security, and keep the database environment available 24/7. A managed database service eliminates the need for onsite IT professionals and administrators to apply security patches, perform routine maintenance, and monitor performance. It also introduces a level of sophistication that many businesses couldn’t manage on their own.
What’s included in a managed database?
Managed database cloud providers like Amazon RDS and MongoDB Atlas offer customers different tiers of services depending on their needs and overall business operations. These can include ready-to-use packages or individual services.
Most managed databases:
- Provide the software that keeps your operations running 24/7.
- Perform automatic backups as needed.
- Manage updates, upgrades, and security patches.
- Scale up or down as needed.
- Encrypt stored data and data in transit.
- Monitor performance and send alerts.
- Optimize processes for best performance.
- Eliminate the need for on-premises infrastructure maintenance.
Types of managed databases: Relational and non-tabular options
Managed database services have become common for all kinds of purposes—from food delivery apps to e-commerce businesses to Google searches. While managed databases come in many forms, two main categories are often discussed: relational (usually SQL-based) and non-tabular or non-relational (non-SQL databases) often grouped under the NoSQL umbrella.
Others include document databases like MongoDB, wide-column stores like Cassandra, graph databases like Neo4j, time-series databases, vector databases, and key-value stores. Each has distinct design trade-offs, optimized for different kinds of workloads and data models.
Let's take a closer look at relational and NoSQL managed databases.
Relational managed databases
Relational databases are table-based and organize information in a fixed structure, making it easy to see how different data points are connected. They’re a good fit when you need consistency—for example, in financial records where every transaction must include the same fields like date, amount, and account number.
What makes them unique:
- Use SQL to query and update data
- Depend on strict, predefined rules, which ensures accuracy but can make changes more difficult
- Organize data in tables with rows and columns
- Offer many popular options, such as SQL Server, MySQL, and PostgreSQL
NoSQL managed databases
NoSQL databases are more flexible with how they organize information. Unlike relational databases that require a rigid schema, NoSQL databases accept data types without a predefined structure. This flexibility is handy for varied content like social media posts (where one post might contain text, and another, photos and videos) and applications that must scale rapidly, often requiring on-the-spot adjustments.
What makes them unique:
- Offer four main types of NoSQL databases: document, key-value, wide column, and graph
- Can handle structured, unstructured, and semi-structured data (e.g., documents, videos, photos), because a fixed structure isn’t required
- Are built for resiliency, since they spread data across multiple servers instead of relying on just one
- They’re flexible—you can add new types of data without redesigning the whole database
How to choose the right managed database for you
Choosing between database types depends more on your specific requirements and constraints than simply whether your data is "structured" or "unstructured." Both relational and NoSQL databases can handle structured data effectively, but which one you choose may depend on a variety of factors.
Databases that use SQL language often:
- Keep a consistent data structure over time.
- Contain data that fits in a normalized, table-based structure with well-defined relationships.
- Run complex queries, including multiple JOINS across related tables.
- Work best when teams have SQL expertise and are already relying on relational databases.
NoSQL databases (including document databases like MongoDB) often:
- Scale easily across multiple servers.
- Use flexible schemas that can evolve over time.
- Deliver high performance at large scale.
- Store data in formats that align closely with application objects.
Take a closer look at your data needs
When it's time for you to explore your options, it's a good idea to start by asking yourself a series of questions to determine your needs, pain points, and whether you should choose a relational or NoSQL solution. The questions below are a good place to start.
Assess your data:
- How structured is your information?
- How often does it change?
- What relationships exist between data elements?
Evaluate your performance needs:
- Do your queries need to meet specific time specifications?
- Are your traffic patterns steady or unpredictable?
- Do you foresee the need to scale up or down with short notice?
Consider your AI and modern application requirements:
- Do you need semantic search or AI-driven recommendations?
- Will you be storing vector embeddings alongside user data or metadata?
- Do you want to integrate AI features into your main application without maintaining a separate vector database?
- Are you building features that combine traditional data operations with machine learning, generative AI, or natural language interfaces?
Modern managed databases like MongoDB now support both traditional transactional workloads and AI/vector operations in a single platform, eliminating the need to maintain separate systems for analytical and operational data.
Address your security and cost requirements:
- Do you require industry-specific regulations (HIPAA, PCI DSS, etc.)?
- Do you handle sensitive data?
- Are you exploring pay-as-you-go plans and ad-hoc services?
- Have you identified hidden costs?
How to get started with managed databases
After you’ve explored your data needs and answered the essential questions above, it’s time to take the next step. Below is a high-level plan that can put you on the path to implementing a managed database.
Choose your database
Will you use relational or NoSQL databases? Many managed database providers support both types, so you can pick one that best fits your needs.
Plan your move
If you need to transfer existing data from an on-premises database, most providers can help with tools that automate the process. For example, MongoDB offers Relational Migrator, a visual tool that simplifies migrating from relational databases to MongoDB by helping you design your new schema and move your data easily.
Before migrating your data, consider breaking it into separate groups so you don't transfer all data simultaneously. This extra step will make troubleshooting easier if something goes wrong. During migration, watch for compatibility issues and keep data exports organized.
Set up your database
Managed services walk you through setup by letting you choose things like how powerful the database should be, how much storage you need, and where it will run. Once you make those choices, you can launch the database with just a few clicks. What used to take weeks with traditional setups now takes only minutes.
Connect your applications
Make sure your current system will connect with your new service. Consult your provider's help tools, contact their service desk, or ask your internal IT team for assistance, if necessary. Your provider may offer code samples and software development kits (SDKs) to help with this effort, as well.
Configure access and security settings
Set up user permissions and roles to control who can read or edit your data. Security settings include encryption, firewalls, and automated backups to protect against data breaches and other cyber threats. Most providers offer these features as part of the setup process.
Monitor and optimize performance
When your database goes live, be sure to sign into the provider's dashboard. Most managed database services offer built-in monitoring tools, such as dashboards to track use, detect slow responses, and adjust performance settings.
Scale as you grow
One of the most attractive features of a managed database is the ability to scale quickly. Whether adding users, storing more data, or handling spikes in traffic, most database management services allow you to increase capacity immediately, ensuring scalability and high availability with little or no downtime.
Key things to consider when seeking stakeholder approval of a managed database service provider
As you start narrowing down database options, you’ll likely find yourself fielding questions from your technical team, stakeholders, and decision-makers. The questions highlighted below often come up in discussions with colleagues when considering managed databases. Knowing where you stand on each one can help the approval process go more smoothly.
Do we need to know how to code to use a managed database?
Not necessarily. Most managed database services are built for those without a technical background and offer many self-help options, such as setup guides, visual dashboards, and helpful defaults so you can get started without coding.
Is a managed database the same as storing files in the cloud?
Not quite. Services like Google Drive are designed to hold files, such as documents, photos, and videos, while a managed database stores structured information like user profiles, product details, or transaction histories.
Can we switch between relational and NoSQL databases later?
Not always. Changing from relational to NoSQL means rethinking how your data is organized and then migrating it from one system to another. This is why understanding your data needs early on is so important.
How do we know if a managed database is right for our company?
If your project involves storing and retrieving data—and you’d prefer not to manage backups, updates, or security patches yourself with a self-managed database—a managed database can be a smart choice. It removes much of the day-to-day complexity, letting you focus on what your application does rather than how it runs.
Are managed databases secure?
Yes. Most providers include strong security measures to ensure your data is secure, but no system is completely risk-free. However, a managed database system offered by a cloud service provider employs security experts, meaning they can handle cybersecurity breaches and threats better than you might be able to handle them on your own.
Conclusion
Managed databases have removed much of the complexity of setting up and maintaining database systems. They are classified according to your needs (relational and NoSQL), automate most tasks that would require constant oversight using a self-managed database, and give you the flexibility to scale quickly.