Four Main Types of Databases Explained (2025)

Why Understanding Database Types Matters in 2025

In today’s digital-first world, databases are the invisible engines powering everything from your favorite apps to enterprise-level data systems. But not all databases are built the same. Whether you’re a developer, data analyst, or a business owner evaluating tools like Baserow, understanding the different types of databases and how they’re used in 2025 is crucial.

With growing needs for storing and managing unstructured data, real-time access, and cloud scalability, the landscape of database technology has evolved rapidly. In this guide, we’ll explore the four main types of databases, how they work, and where they fit in the modern tech stack. We’ll also highlight how tools like Baserow are helping users handle data management in more visual, collaborative ways—no SQL skills required.

What Is a Database? (+ How Databases Store Data)

At its core, a database is an organized collection of data that can be easily accessed, managed, and updated. From small local applications to enterprise systems, databases store information in various formats—from structured rows and columns to unstructured or semi-structured documents.

But a key distinction lies in how the data is stored, retrieved, and related. Some databases use structured tables (like spreadsheets), while others are designed for handling complex relationships (e.g., social networks or supply chains). With advances in cloud databases, storing large volumes of distributed data has also become easier and more affordable.

Whether you’re working with financial records, user profiles, or IoT data streams, choosing the right type of database is essential for performance, scalability, and security.

Types of Database Management Systems (DBMS)

A Database Management System (DBMS) is software that enables users to query data, add, modify, or delete records, and enforce data rules. It acts as the middle layer between the user and the actual data stored in the database.

Here are 7 common types of DBMS:

1. Hierarchical DBMS

• Data is organized in a tree-like structure.
• Used in legacy systems like IBM Information Management System (IMS).
• Great for applications with one-to-many relationships.

2. Network DBMS

• More flexible than hierarchical; allows many-to-many relationships.
• Not widely used today but relevant in older systems.

3. Relational DBMS (RDBMS)

• Data is stored in tables with rows and columns.
• Most popular type (e.g., MySQL, PostgreSQL, Oracle).
• Supports powerful querying through SQL.

4. Object-Oriented DBMS (OODBMS)

• Stores data as objects, similar to OOP programming.
• Ideal for applications with complex data and behavior.

5. NoSQL DBMS

• Designed to handle semi-structured or unstructured data.
• Includes document, key-value store, column-family, and graph databases.

6. Cloud DBMS

• Hosted in the cloud; scalable and accessible over the internet.
• Examples include Amazon Aurora, Firebase, and Google Cloud Spanner.

7. In-Memory DBMS

• Stores data in RAM for faster performance.
• Ideal for real-time applications (e.g., Redis).

💡 Baserow, while often categorized as a relational-like database, provides a no-code interface for collaborative data management, combining the ease of spreadsheets with the power of databases.

The 4 Main Types of Databases (with Examples)

Now that we’ve covered how data is managed through DBMS, let’s explore the four main types of databases you’ll encounter in 2025:

1. Relational Databases (SQL-Based)

Relational databases are the most widely used, especially for systems requiring strong consistency and structured data.

• Structure: Data is stored in tables (relations) with rows and columns.
• Example Tools: MySQL, PostgreSQL, Oracle Database, SQL Server.
• Ideal For: Financial systems, inventory management, CRM platforms.
• Query Language: SQL (Structured Query Language) to query data.
• Strengths: Integrity, schema enforcement, support for complex relationships through foreign keys and joins.
• Limitations: Less suited for handling unstructured or semi-structured data or horizontal scaling.

📌 Baserow provides a spreadsheet-like interface but stores data in a relational format, allowing you to define relationships between tables without writing SQL.

2. NoSQL Databases

“NoSQL” stands for “Not Only SQL” and includes databases designed to handle flexible data models.

There are four types of NoSQL databases:

1. Document-Oriented

• Stores data in JSON-like documents.
• Example: MongoDB, CouchDB.

2. Key-Value Stores

• Simple and fast: each item is stored as a key and a value.
• Example: Redis, DynamoDB.

3. Column-Family Stores

• Organize data in columns instead of rows.
• Example: Apache Cassandra, HBase.

4. Graph Databases

• Focus on complex relationships and connections between data points.
• Example: Neo4j, Amazon Neptune.
• Ideal For: Social networks, recommendation engines, real-time analytics, IoT.
• Strengths: Scalability, flexibility, high performance with unstructured data.
• Limitations: Often no strict schema; may lack support for complex transactions.

⚡ If your project involves flexible schemas or semi-structured data, a NoSQL database may be the way to go.

3. Object-Oriented Databases

These databases store data as objects, similar to how programming languages like Java or Python define classes and objects.

• Structure: Objects contain both data and the methods to manipulate that data.
• Example Tools: db4o, ObjectDB.
• Ideal For: Applications built with object-oriented codebases; CAD, multimedia, simulations.
• Strengths: Seamless integration with OOP paradigms.
• Limitations: Less common in mainstream use; smaller ecosystem.

4. Hierarchical Databases

One of the oldest database types, where data is stored in a tree-like structure.

• Structure: One parent node can have many child nodes, but each child only has one parent.
• Example Tools: IBM Information Management System (IMS).
• Ideal For: Legacy systems, file systems, org charts.
• Strengths: Fast for specific read operations with predictable paths.
• Limitations: Inflexible structure; poor support for many-to-many relationships.

Additional Database Types to Know in 2025

While the four main types dominate most use cases, there are other database types worth knowing in today’s diverse data landscape. These don’t always fall neatly into a single category but are crucial in modern data management scenarios:

Operational Databases

Used to manage dynamic data in real-time applications. Think of these as the workhorses behind logistics systems, banking apps, and retail POS software.

• Purpose: Continuously process transactions and updates.
• Examples: SAP HANA, Microsoft Azure Cosmos DB.
• Ideal For: High-volume environments needing real-time reads and writes.

Cloud Databases

Hosted in the cloud, these databases provide scalability, flexibility, and lower maintenance compared to traditional setups.

• Examples: Amazon RDS, Google Cloud SQL, Firebase.
• Benefits: Elastic scaling, global availability, managed services.
• Use Case: Startups and enterprises adopting serverless architecture or managing distributed teams.

Distributed Databases

Designed to run on multiple machines, they allow for improved fault tolerance and data redundancy.

• Examples: CockroachDB, Apache Cassandra.
• Advantage: Data is distributed across nodes for speed and resilience.

These types often overlap with NoSQL or relational structures, and some platforms (like Baserow) are built to be cloud-ready and horizontally scalable for growing teams and data sets.

How Baserow Fits into Modern Data Management

If you’re looking for a flexible, collaborative, and open-source database tool in 2025, Baserow is an excellent choice.

Unlike traditional databases that require SQL skills or developer resources to set up, Baserow empowers anyone—technical or not—to build, manage, and share databases visually. It blends the simplicity of spreadsheets with the power of relational databases, making it an ideal platform for:

• Startups looking to organize data quickly without backend complexity.
• Business teams managing workflows, projects, or CRM data.
• IT departments needing full control through self-hosting.
• Developers looking to build custom apps on top of structured, collaborative data.

Key Features:

• Relational database engine with linkable tables.
• Built-in collaboration tools.
• REST API and plugins for customization.
• Option to self-host for full data control or use the cloud version.
• Ideal for managing semi-structured data, customer lists, product catalogs, and more.

💡 While Baserow aligns most closely with relational database principles, its visual interface and API make it easy to extend into other use cases—without needing to write a single line of SQL.

Choosing the Right Database for Your Needs

Picking the right type of database depends on your data structure, scalability needs, technical skills, and budget. Here’s a quick cheat sheet:

If you’re just getting started, tools like Baserow can bridge the gap—offering the power of databases without the traditional learning curve.

Try Baserow: Modern, Scalable, Open-Source Data Management

In a world where data is more valuable than ever, the tools we use to manage it shouldn’t hold us back. From structured customer databases to fast-growing product inventories or operational workflows, choosing the right database solution has a direct impact on your team’s efficiency, scalability, and innovation potential.

Yet, many traditional database platforms come with steep learning curves, expensive licensing, and limited flexibility. That’s where Baserow steps in.

Baserow is a modern, open-source alternative to complex database systems. It’s built for non-technical teams, developers, and IT professionals who want the power of a database, without the friction of traditional tools. Whether you’re managing semi-structured data, collaborating on projects, or building internal tools, Baserow gives you a user-friendly interface that feels like a spreadsheet—while operating as a fully functional relational database behind the scenes.

Why Choose Baserow in 2025?

• No-code interface for building databases visually
• Support for relationships between tables (like a real DBMS)
• Designed for storing and managing unstructured or semi-structured data
• Fully open-source, so you can self-host and control your data
• API access, automations, and plugin support for custom workflows
• Scalable from solo makers to enterprise teams
• A powerful way to bridge the gap between spreadsheet simplicity and database sophistication

Baserow is a flexible choice for 2025 and beyond. It works well whether you run a startup, improve team operations, or move from Airtable or spreadsheets. It helps you manage your data the way you want—without sacrificing control, customization, or scalability.

And unlike legacy systems, you won’t need to worry about complicated onboarding or hiring developers just to manage your data. Baserow gives power back to the user, offering a clear path from idea to execution—fast.

🔍 If you are still not sure what type of database is right for you:

Start simple. Start visual. Start with Baserow.

You don’t need to know SQL. You don’t need to be a data architect. You just need the right tool to help your team organize, structure, and query data—all in one place.

👉 Try Baserow today — it’s free, open-source, and ready for your next data project.

Try Baserow today