10 examples of databases that will support the growth of your information system

Too often, databases are seen as a purely technical subject, reserved for IT experts. They're seen as a basic infrastructure that has to work, period.

This is a mistake, because the volume of corporate data is growing exponentially: customer data, product data, transaction data, logs, connected objects, social networks, and so on. The ability to harness this data effectively will become a key competitive advantage, if not a condition of survival for SMEs and SMIs.

Of course, not every SME is destined to become a "data company". But every company can and should make progress in exploiting its data, at its own pace and according to its own means.

To help you achieve this, here are 10 examples of the most effective databases in 2025.

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What is a database?

In its broadest sense, a database is a structured collection of information, managed by a specific software program known as a database management system, or DBMS.

It is an absolutely central element of any company's information system, whatever its size.

In concrete terms, databases enable the storage, organization and efficient use of all vital company data: customers, products, orders, employees, suppliers, inventories, production data, financial and accounting data, etc. They are at the heart of all applications and processes. They are at the heart of business applications and processes.

Without a database, it's impossible to manage your business computerized! Here are just a few examples

• CRM (customer relationship management) is based on a customer database;
• ERP (enterprise resource planning) uses product, inventory, purchasing, HR and other databases;
• the e-commerce web store uses a product catalog and customer accounts;
• decision-making tools and dashboards draw on company data.

In addition to these "traditional" uses, companies are now seeking to leverage their data to make better decisions, personalize their offers and optimize their operations. Each on its own scale. They are also facing regulatory compliance issues, particularly with the RGPD. A data leak can be very costly in terms of image and sanctions!

In a nutshell: good database management is both an operational imperative and a strategic issue (development and transformation). That's why the subject is so high on organizations' IT agendas.

What are the 4 types of database?

1. Relational databases (SQL)

Databases are said to be " relational " when data is stored in tables made up of rows (records) and columns (attributes).

Each table has a unique primary key. Foreign keys are used to link tables together, in order to model relationships.

☝️ SQL has become the standard for relational databases.

Today, relational databases are the most mature. Oracle is the leader on the professional market, with advanced functions, followed by Microsoft's SQL Server. They are at the heart of critical business applications such as :

• management (ERP, CRM, finance, HR, purchasing, logistics and production apps) ;
• payment and reservation systems (banking, e-commerce, travel);
• medical records, insurance, administration, specific business applications.

Despite their maturity, relational databases are showing their limitations in the face of certain modern needs: modeling complex data, distributed processing of large volumes, real-time queries, etc.

2. Document-oriented databases

Here, the focus is no longer on data, but on collections of documents. Databases are therefore tailored to manage semi-structured and heterogeneous data, following dynamic schemas, with greater flexibility and performance.

A document encapsulates data in key-value format, often in JSON, XML or BSON (binary JSON). It may contain fields of various types, lists or nested documents. Each document then has a unique identifier.

Concrete use cases for these document-oriented databases :

• articles in a content management system (CMS) ;
• product catalogs ;
• user profiles;
• games in the form of web and mobile applications.

3. Column-oriented databases

These share common features with the relational model (tables, rows, columns), but adapt them for Big Data and queries on immense volumes. The key: storage by columns rather than rows. Columns from the same family are stored contiguously together.

Columnar storage, coupled with compression, partitioning and data/query distribution mechanisms, enables high scalability.

Google, with its Bigtable solution (and its free HBase version), and Facebook, with Cassandra, are the references in this field.

Here are the most important use cases:

• data warehouses ;
• distributed processing (MapReduce) ;
• Internet of Things (IoT);
• log analysis.

4. Graph databases

These use graph theory to model entities (nodes) and the relationships (edges) between them. Typically, banks use graph databases to identify suspicious transaction patterns. For example, if a customer suddenly makes several transactions to newly-created accounts, which in turn quickly transfer these funds to a foreign account, the relationships between the nodes trigger an alert.

With graph databases, we can efficiently explore complex, multi-level relationships that are difficult to model or query in traditional databases.

They have become central to :

• social networks (relationships between users) ;
• recommendation systems ;
• fraud detection;
• network analysis, with identity and access management.

10 examples of efficient databases in 2025

Here's a clear overview of the 10 must-have solutions in 2025, with their strengths and weaknesses, to help you make an informed choice based on your real needs.

Oracle Database

This is one of the benchmark solutions for enterprise databases. Oracle Database offers reliability and security, making it the ideal choice for mission-critical applications. However, this excellence comes at a cost, which is not justified for companies with less demanding needs.

👍 The benefits :

• Data always consistent: your sensitive information is protected by proven mechanisms, even in the most complex environments.
• Holds up under pressure: even during peak loads, Oracle maintains highly competitive response times. This is made possible by intelligent optimizations that you configure on demand.
• Never (or almost never) down: even when hardware fails, automatic failover and replication mechanisms ensure that your applications keep running.
• Data safe: sophisticated encryption, auditing and access controls protect your sensitive data. In turn, this level of security simplifies your regulatory compliance.
• Uncompromising analysis: everything runs directly in the database, from simple SQL queries to machine learning. No need for additional infrastructure.

👎 Disadvantages:

• Substantial investment : it's no secret that Oracle licenses and infrastructure represent a significant budget. It won't be justified for medium-sized structures with no critical needs.
• Requires experts: without qualified people to maintain it, you'll only exploit a fraction of this database's capabilities... while paying a high price.

Oracle Database

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Microsoft SQL Server

SQL Server is the Swiss Army knife of the Microsoft ecosystem.

If your company already uses Windows, Office and Azure, SQL Server will integrate naturally into your environment, with minimum friction.

👍 Benefits:

• Integrates seamlessly into the Microsoft ecosystem: communication is natural - authentication, reporting, cloud. No complex development required.
• Fast when you need it: innovative technologies accelerate both fast transactions and high-volume analyses, without separate systems.
• Always available: partitioning mechanisms ensure continuity, even during upgrades or incidents, limiting the impact on your business.
• In-depth protection: sophisticated encryption and access controls secure your data, without compromising performance.
• Intuitive even for beginners: Microsoft sets the standard for clear graphical interfaces and intelligent wizards to guide you. Even if you're not a database expert, you'll be able to work with ease.

👎 Disadvantages:

• Pricing to be decoded: with Microsoft, take the time to fully understand what you're buying. Affordable versions come with a whole range of feature-restricted editions.
• Long-term marriage: once integrated into your Microsoft infrastructure, a change of course will become costly and technically complex.

Salesforce Data Cloud

Salesforce is the specialist in customer data.

If you're all about personalized customer experience and already use Salesforce, CDP (Customer Data Platform) Data Cloud software will give you a significant competitive edge.

👍 The benefits:

• Centralization of multi-source data: Salesforce Data Cloud collects and aggregates data from CRM, ERP, e-commerce, social networks and other sources.
• Real-time analysis: immediate processing and analysis of data flows, for instant decision-making and greater responsiveness.
• Advanced segmentation and personalization: thanks to AI, the solution creates dynamic profiles and enables ultra-targeted campaigns based on customer history and behavior.
• Omnichannel campaign management: synchronization and coordination of marketing messages across all channels, for seamless communication.
• Friction-free integration with the digital ecosystem: Salesforce offers native connectors for tools such as Tableau, Slack, Google BigQuery or Snowflake, ensuring optimal interoperability.

👎 Disadvantages:

• Unsuitable for small structures: functional coverage and pricing will be more suitable for large enterprises and SMEs mature on the subject of databases.
• Gradual learning curve: mastering all modules requires time and training. So plan this investment from the outset.

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MariaDB

The free, scalable alternative to MySQL.

For those who want to move away from proprietary systems, without sacrificing performance, MariaDB offers a smooth transition with a bonus of innovation.

👍 Benefits:

• Painless migration: your MySQL applications will work with MariaDB, without rewriting.
• Faster by default: optimizations naturally reduce response times on large volumes, without complex configuration on your part.
• Security at no extra cost: solid protection is built into the standard version. No need to pay for additional modules.
• Rich functionality: advanced capabilities are included free of charge. This saves you the hassle of tinkering with expensive alternative solutions.
• Total transparency: development is open. So you understand where the product is going and can influence its evolution, unlike proprietary solutions.

👎 Disadvantages:

• Compatibility to be checked: some specific functions of recent MySQL may not work. Test your critical applications before migration.
• Growing community: there are fewer tools and experts available than for MySQL, although the gap is closing fast.

MongoDB

MongoDB has rapidly gained market share in the web and mobile worlds. It is currently the benchmark for document-oriented databases. Ideal for fast-moving applications handling heterogeneous data!

👍 The benefits :

• Maximum flexibility: you can store data with varied and evolving structures without restructuring the base. Perfect for projects that pivot frequently.
• Accelerated development: natural correspondence with code objects eliminates complex translation layers and reduces time-to-market.
• Native speed: the document-centric approach avoids costly joins and drastically accelerates operations, even on millions of records.
• Frictionless growth: simply add servers as your needs grow. MongoDB automatically distributes the load without manual intervention.
• Robust ecosystem: professional training, support and tools mean you don't have to navigate blindly, especially for mission-critical deployments.

👎 Drawbacks:

• Not made for banking: support for multi-document transactions remains limited. Avoid for mission-critical financial applications.
• Think outside the box: designing efficient data models requires a different approach to SQL databases. A period of adaptation is therefore required.

MySQL

For years, MySQL has been the Swiss army knife of the Web.

Simple, proven and universally supported, this database is often the default choice for small to medium-sized websites and applications.

👍 The benefits :

• Simplicity first: installation in just a few minutes, highly intuitive administration. You'll be up and running immediately, even without advanced expertise.
• Fast to read: MySQL is particularly efficient for serving web content, which explains why most CMS have adopted it.
• Rock-solid stability: decades of intensive use have eliminated most bugs. Your database won't let you down in production.
• Everywhere you go: natively supported by all web languages and frameworks, with abundant documentation and millions of trained developers.
• Low budget: it's free for most uses!

👎 Disadvantages:

• Glass ceiling: performance drops on very large volumes or complex queries. Plan for migration in the event of strong growth.
• Not for intensive use: lock management is less sophisticated and can slow down applications with many simultaneous writes.

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PostgreSQL

This is a premium open source alternative when you need advanced functionality but can't afford to invest in Oracle. PostgreSQL promises a comparable level of sophistication... without the prohibitive costs.

👍 The benefits:

• Power to spare: built-in enterprise features mean you don't have to buy expensive add-ons or develop workarounds.
• Future-proof code: strict adherence to SQL standards protects your development investments over the long term.
• Infinitely adaptable: its modular architecture lets you add exactly the capabilities your business needs. No overload.
• Native multi-functionality: integrated support for structured data, documents, text search and geolocation simplifies your architecture.
• Institutional security: protection and integrity mechanisms are already adopted by the most demanding banks and administrations.

👎 Disadvantages:

• More technical: PostgreSQL requires more expertise than MySQL to be perfectly optimized.
• Priority to reliability: it is slightly slower on certain simple operations, prioritizing data consistency over raw performance.

Redis

Redis is the champion of speed.

For projects that pay attention to every millisecond of processing time saved, this database offers first-rate performance. Example: for datas requiring instant access, such as caches and counters.

👍 Advantages:

• Ultra-fast: microsecond responses transform the user experience of your most time-sensitive applications.
• Tailored structures: specialized data types simplify the creation of functionalities such as rankings, queues or counters.
• Integrates everywhere: a simple API plugs easily into your existing system, without requiring a major redesign.
• More than just a cache: advanced capabilities such as scripting, clustering and replication make this a far more versatile tool than it seems.
• Industrialized: professional support with an excellent reputation. Solutions hosted by all the major cloud providers simplify its use in production.

👎 Disadvantages:

• Volatile by design: storage is mainly in memory, which can lead to data loss in the event of an unexpected reboot.
• Limited by RAM: you'll need to have enough memory to hold all the data. Costs can rise rapidly for large volumes.

SAP HANA

SAP HANA is an analytical gas factory, designed for large enterprises that need to analyze huge volumes of data in real time.

The solution stands out for its speed and depth of analysis.

👍 Advantages :

• All in memory: a revolutionary architecture eliminates the disk bottleneck and drastically accelerates all processing, even the most complex.
• Instant analysis: reports and dashboards run in real time on fresh data, without waiting for overnight extractions.
• Comprehensive toolbox: benefit from integrated machine learning and text mining capabilities. No need for additional solutions!
• Integrates with everything: extensive connectivity facilitates integration with your existing ecosystem, whether SAP or not.
• Designed for the extreme: SAP architecture is capable of handling terabytes of data with constant responsiveness.

👎 Disadvantages:

• Major investment: the cost is very high in terms of hardware, licenses and expertise. It is therefore only justifiable for large organizations.
• Inherent complexity: a significant learning curve, even for experienced professionals. Serious support is required.

SQLite

It's a pocket database, a minimalist package.

If you need to store structured data locally, without a server or configuration, SQLite offers a surprisingly robust solution.

👍 Advantages:

• Extremely lightweight: it's a simple file that you can embed in any application without installation or server.
• Perfect for the edge: works directly on connected devices and objects, allowing data to be processed as close as possible to its source.
• Surprisingly robust: internal mechanisms protect your data, even in the event of a power failure or system crash.
• Local speed: surprisingly high performance for moderately-sized local data, often superior to more complex client-server solutions.
• Universally supported: the tool is natively integrated into most languages and systems, with a simple API.

👎 Disadvantages:

• Not for multi-users: SQLite is designed for sequential or limited access, not for hundreds of simultaneous connections.
• Limited by its simplicity: it's unsuited to large databases (>10 GB) or distributed architectures requiring more sophisticated solutions.

How to choose your database? 5 criteria to consider

#1 The nature and volume of the data to be managed

• What is your data model? Structured, semi-structured, documents, graphs...
  👉 Example: for data on e-commerce product profiles, a document database like MongoDB will be more suitable than a relational database.
• Growth and variability? Linear, incremental, seasonal peaks? MB, GB, TB?
  👉 Example: to handle peaks like Black Friday, Redis will be very effective as a cache in front of a main database.

#2 Processing

• What are the use cases? Heavy transactional, analytical, decision-making, real-time?
  👉 Example: for complex BI queries, a data warehouse will be more suitable than a MySQL database.

#3 Environment and security

• What is your application ecosystem? Languages, frameworks, ETL/BI tools, virtualization, cloud?
  👉 Example: in a context with Microsoft applications, SQL Server will integrate more easily than an open source base.
• What are the legal and security constraints? RGPD, regulated sector, encryption, auditability?
  👉 Example: in the healthcare sector, a database like Oracle, which is HIPAA/RGPD certified, is essential.

#4 Maturity and longevity

• How old is the solution? Has it been adopted by the market? How dynamic is it?
  👉 Example: MongoDB has gone beyond its hype status to become a sure thing.
• How rich is the ecosystem? Libraries, integrations, tools, hosting providers?
  👉 Example: the MySQL/PostgreSQL ecosystem is currently the largest and most dynamic.

#5 Budget and skills

• What is the license/subscription model? Its initial cost and TCO over 3 years? 👉 Example: SQL Server is free with the Express edition, but the Enterprise edition costs several thousand euros.
• What skills are available in-house? On the market? How much do they cost? What training is available?
  👉 Example: it's easier and cheaper to find PostgreSQL developers than SAP HANA experts.

FAQ: frequently asked questions about databases

How do I choose between relational and NoSQL?

It's not a question of choice. It's not a question of pitting SQL against NoSQL. Most applications combine SQL for the transactional core and NoSQL for more specific needs. The key is to have the APIs and tools to manage this complementarity.

SQL remains indispensable for structured data and processing where consistency and integrity are paramount. Relational databases such as PostgreSQL are excellent for this.

NoSQL, on the other hand, provides flexibility and performance for large volumes of varied data (documents, graphs), often with less consistency. MongoDB is a benchmark.

Is it better to migrate to the cloud or stay on premise?

That depends on your context and IT strategy. The cloud brings simplicity of administration and an attractive pay-as-you-go model, but raises questions of long-term costs, security and compliance.

For a start-up or a new project, a native cloud approach is often the best way to focus on the business.

For an industrial SME, a hybrid approach is generally preferable, keeping sensitive data in-house and using the cloud for occasional processing.

Should I opt for open source or vendor solutions?

Open source offers independence, low initial costs and a rich ecosystem. Databases such as MySQL, PostgreSQL or MongoDB are de facto standards that most companies consider sufficiently robust. Open source is no longer synonymous with immaturity. If you have a motivated team of experts, open source will bring you greater control and agility.

Vendor solutions offer additional guarantees, advanced functionalities (security, encryption, availability), responsive support and sector-specific certifications.

Oracle and SQL Server are still the safe bet for business-critical applications.

What disruptions can we expect to see in databases over the next 3-5 years?

Over the next 3-5 years, several major developments will transform the database landscape:

• Artificial intelligence (AI) will become native to databases. Instead of exporting your data to separate AI tools, you'll be able to query your data in natural language and get relevant answers.
  
  
• LLM-based interfaces will enable you to automatically generate complex queries, intuitively explore data and program models. All without the need for in-depth technical expertise.
  
  
• Serverless databases will become commonplace, eliminating the need to scale resources. The database will automatically adapt to your needs, going into standby mode when not in use, and ramping up instantly during peaks in activity. This model radically simplifies administration and significantly reduces costs.

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Example databases: what's in it for me?

A final word. Priority should always be given to usage and business value. In other words, what really counts is how the database supports your business activity, over and above technical considerations (performance, scalability, modernity). A database must help solve real-life problems.

So avoid sterile technological debate. Rather than choosing a technology for its technical features or popularity, choose it for its suitability to your specific needs!