What is PostgreSQL?

Introduction

Those who come from the world of MySQL or MariaDB are well aware of the importance of a relational database management system (RDBMS) in managing data for web applications and enterprise systems. However, in the open source database landscape, beyond MySQL and its forks, there is another solution that has gained increasing importance over the years: PostgreSQL.

PostgreSQL is not just an alternative, but a true point of reference for those looking for solidity, adherence to SQL standards, advanced extension capabilities and an enterprise level that is often compared to systems like Oracle Database.

In this article, we'll explore its history, its evolutionary history, its current status, its advantages over MySQL and MariaDB, its licensing model, and finally its positioning as a direct competitor to high-end commercial databases.

From academic origins to open source project

The history of PostgreSQL has its roots in the 80s at the University of California, Berkeley , a context that gave birth to several fundamental projects for modern computing. During those years, Professor Michael Stonebraker and his research team were busy exploring new frontiers for data management systems, at a time when the very concept of a relational database was moving beyond the realm of pure theory to become a practical technology used in academia and industry.

Even before PostgreSQL was born, Ingres , one of the first full-featured relational database management systems , was developed in Berkeley . Ingres was a pioneering project that introduced decisive conceptual innovations and, in addition to providing an experimental environment for academia, became the benchmark for many companies. It's no coincidence that several subsequent SQL dialects and products were directly inspired by Ingres, making it a true milestone.

However, over time, Ingres's architectural limitations emerged , especially in handling non-traditional data types and meeting the new needs of increasingly complex applications. To address these challenges, Stonebraker launched a new project called POSTGRES (literally "Post-Ingres"), designed to represent a natural evolution and overcome the technological barriers of its predecessor.

The new DBMS was characterized by ambitious goals and a highly experimental approach. The key points of the POSTGRES project were:

• Support for complex data types, far beyond the simple integers and strings handled by traditional relational databases.
• Extensibility of the relational model, thus allowing the addition of new operators, functions, and even user-defined data types.
• Advanced transaction and constraint management, with the aim of ensuring greater robustness, reliability and accuracy in data storage.

POSTGRES was first released to the academic community in 1989 , and continued to evolve and spread among researchers and developers over the next few years. The underlying idea was to provide a living laboratory for the study of databases, while maintaining a practical approach that would allow the software to be used in real-world applications.

A turning point came in 1994 , when the project abandoned its original query language, PostQUEL , in favor of SQL , which was becoming the international reference standard. This move marked the beginning of the project's true adoption outside of purely academic circles, because it made POSTGRES compatible with a language now familiar to professionals and businesses.

The release of the new version was called Postgres95 , a clear reference both to its predecessor and to the desire to open the project to a wider audience. The decision to distribute the software as open source was another key factor: for the first time, independent developers and companies from around the world could access the code, contribute to its improvement, and adapt it to specific scenarios.

A few years later, in 1996 , with SQL support now well established, the project took on its definitive name of PostgreSQL . The new name retained its connection to the Postgres legacy, but also emphasized full adherence to the SQL standard.

Since then, PostgreSQL has embarked on a path of constant growth, driven by an active community and supported by developers and companies who believed in its evolution. This synergy has allowed the project to transform, over time, from a university initiative to a recognized pillar in the world of open source relational databases.

Evolution over time

PostgreSQL's history hasn't been a sudden surge in popularity, but rather a gradual journey of continuous improvements and a constant focus on stability and innovation. Each phase has helped cement its reputation, making it one of the pillars of the relational database ecosystem today.

2000s: Solidity at the Center

In the early 2000s, PostgreSQL focused primarily on two fronts: stability and performance . The development community introduced Write-Ahead Logging (WAL) , a technology that guaranteed greater data security in the event of a crash or unexpected interruption. This innovation greatly strengthened the perception of PostgreSQL as a reliable system in production , capable of competing with commercial solutions.

This phase also laid the foundations for features that would become indispensable in the following years, such as improved indexing and transaction management in complex scenarios.

2005 – 2010: The era of enterprise features

In the second half of the 2000s, PostgreSQL began incorporating features typically associated with enterprise-level databases . Among the notable innovations was Point-In-Time Recovery (PITR) , which allowed the database to be restored to a specific point in time, essential for mission-critical environments.

Another important step was the introduction of partitioned tables , which allowed for the management of increasingly larger datasets without losing efficiency. Indexing was also significantly improved, with the arrival of new algorithms and search methods that made queries faster and more scalable.

Thanks to these innovations, PostgreSQL stopped being seen as just an “academic” or “open source” solution and began to attract the attention of companies that until then had focused exclusively on commercial products.

2010 – 2015: Expansion through extensions

The next five years were characterized by a huge push towards modularity and extensibility . PostgreSQL gradually transformed into a platform capable of adapting to different usage scenarios, thanks to the ability to add extensions.

During these years, components were developed that are now considered true pillars of the PostgreSQL ecosystem. One of these was PostGIS , the extension that transformed the database into a reference system for geographic data management (GIS). At the same time, Full-Text Search was introduced , which allowed for the implementation of advanced text search capabilities without the need for external solutions.

This phase established the versatility of PostgreSQL: no longer just a traditional RDBMS, but a platform capable of evolving according to the needs of developers and companies.

From 2016 to today: the database for cloud and distributed architectures

In recent years, PostgreSQL has made the definitive leap into the modern world of distributed applications and cloud services. The project has adopted a regular release cycle , with a new major release every year. This predictable and well-documented approach has given companies the ability to confidently plan upgrades, reducing adoption risks.

Among the most significant innovations of this phase we find:

• Parallel query, which uses multiple cores to speed up processing.
• Logical replication, useful for migrations and high availability scenarios.
• JSONB, which led PostgreSQL to compete even with NoSQL databases, offering flexibility without sacrificing relational guarantees.
• A system MVCC (Multi-Version Concurrency Control) increasingly refined, which allows for the efficient management of thousands of concurrent transactions.

Thanks to these features, PostgreSQL is now recognized not only as a solid DBMS, but as a strategic choice for cloud-native environments , large-scale applications and distributed contexts.

The current state

As of 2025 , PostgreSQL is unanimously considered the most advanced open source DBMS in the world , capable of competing not only with open source solutions like MySQL and MariaDB, but also with commercial giants like Oracle Database and Microsoft SQL Server. Its diffusion is no longer limited to technology startups or academic projects: today it is used by banks, government agencies, large web platforms and cloud providers , a demonstration of its maturity and reliability.

The factors that determine its success can be summarised in a few fundamental pillars.

Compliance with the SQL standard

PostgreSQL stands out for being one of the databases most faithful to international SQL standards . This feature minimizes code portability issues and allows developers to write queries and procedures with the certainty that they are compliant with the language rules. For those coming from MySQL, this rigor may initially seem excessive, but in the long run it guarantees a more consistent environment, which avoids syntactic "shortcuts" and limits ambiguity.

Extensibility and flexibility

One of PostgreSQL's most appreciated qualities is its extensible architecture . Users aren't limited to exploiting what's already included in the core, but can define new data types, custom indexes, procedural languages, or functions . This philosophy has made PostgreSQL a platform open to continuous innovation, where every need can be met through extensions without having to wait for official changes to the system core.

An unrivaled wealth of features

PostgreSQL currently offers a range of features that covers both relational and hybrid scenarios. Some notable examples:

• JSON and JSONB: tools that allow you to handle semi-structured documents, making PostgreSQL a true competitor to NoSQL databases.
• Recursive CTE (Common Table Expressions)., very useful for complex queries and hierarchical structures.
• Materialized views, which allow you to save and reuse the result of complex queries, optimizing performance.
• Advanced Indexes such as GIN and GiST, which are essential for text searches, geographic data, and full-text searches.
• Native partitioning and efficient management of large tables.
• Distributed transactions and robust ACID model support.

This richness makes PostgreSQL a suitable choice not only for traditional web applications, but also for complex projects requiring analytics, advanced search, and unconventional data management.

A vibrant community and professional support

The international community supporting PostgreSQL is one of the most active and collaborative in the open source space. Developers constantly contribute patches, documentation, and new extensions, ensuring rapid and secure evolution. Alongside the community, organizations like EDB (EnterpriseDB) offer optimized versions, migration tools, and enterprise support for companies requiring contractual guarantees and SLAs. This balance between community and enterprise has created a healthy ecosystem, capable of satisfying both the open source world and corporate environments.

Cloud availability and global adoption

One of the most obvious signs of PostgreSQL's maturity is its ubiquity in cloud services . All major providers— AWS, Microsoft Azure, Google Cloud —offer PostgreSQL as a managed service, with full compatibility and support for its extensions. There are also optimized variants like Amazon Aurora PostgreSQL or third-party solutions that horizontally scale PostgreSQL for distributed scenarios. This availability has further accelerated adoption, making it the database of choice for those developing cloud-native applications.

PostgreSQL vs. MySQL/MariaDB

Anyone coming from MySQL will immediately notice that PostgreSQL was conceived with a different philosophy . While MySQL was born for simplicity and immediacy—a lightweight, fast, and easy-to-use database for web applications—PostgreSQL has always aimed at full standards compliance , transactional robustness , and a wealth of advanced features . This approach is reflected in a series of substantial differences.

1. Adherence to SQL standards

MySQL is famous for some deviations from SQL standards, tolerated in the name of ease of use. A well-known example is the “elastic” management of GROUP BY, which allows queries that are formally incorrect from an SQL point of view but still produce a result. Similarly, the treatment of values NULL It has some peculiarities that may surprise those who expect strictly compliant behavior.

PostgreSQL, on the other hand, takes a much more rigorous approach , strictly adhering to international standards . This requires a bit more discipline for the developer, but it ensures code portability and reduces the likelihood of ambiguous behavior. In other words, PostgreSQL forces you to write SQL "properly," which is an advantage for complex, long-running projects.

2. Storage model and engines

Another significant difference concerns the storage engine architecture. MySQL has multiple storage engines (InnoDB, MyISAM, Memory, etc.), each with its own strengths and limitations. This flexibility has historically been useful, but it has also led to fragmentation: not all features are available in all engines, and some applications have had to make compromises.

PostgreSQL, on the other hand, uses a single native engine that integrates all the core features. This approach eliminates the need to make tradeoffs and ensures consistent behavior. Furthermore, despite being based on a single core, PostgreSQL allows for extensibility through custom indexes or extensions, achieving a better balance between internal consistency and flexibility.

3. MVCC (Multi-Version Concurrency Control)

Both databases support MVCC, but PostgreSQL's implementation is generally considered more complete and efficient . Thanks to MVCC, PostgreSQL is able to guarantee truly isolated transactions , minimizing heavy locking and allowing multiple users to work simultaneously without conflicts. In MySQL (with InnoDB), the concurrency model is valid but in some cases relies on more restrictive locking, which can impact performance in highly concurrent scenarios. In PostgreSQL, versioning is native and much more fine-grained, making it suitable for contexts with thousands of concurrent transactions.

4. Advanced features

While MySQL was born with a focus on simplicity, PostgreSQL has always aimed to provide an advanced toolset for complex queries and non-trivial scenarios. Some features available natively in PostgreSQL—which arrived late or with less maturity in MySQL/MariaDB—include:

• Recursive CTE (Common Table Expressions)., useful for managing hierarchical data.
• Window functions, essential for analytical calculations and reporting.
• Materialized views, to optimize repeated complex queries.
• Advanced data types such as UUID, JSONB, array and range.
• Extensions: from PostGIS for geographic data to TimescaleDB for time series.

In MySQL, some of these features have been introduced in recent years, but their maturity and overall integration have not yet reached the level of PostgreSQL.

5. Replication and scalability

On the replication front, MariaDB has brought interesting innovations such as Galera Cluster , which allows for real-time multi-master replication. However, PostgreSQL has developed an extremely robust ecosystem:

• Physical replica for high availability scenarios.
• Logical replication for more complex use cases, such as selective migrations or synchronizations.
• Solutions like owners, which simplify the management of HA clusters.
• Extensions like Citus, which transform PostgreSQL into a distributed and horizontally scalable database.

In other words, PostgreSQL doesn’t just provide replication tools, but offers a full range of solutions covering everything from automatic failover to large-scale sharding.

6. Ecosystem and tooling

MySQL has enjoyed a more mature ecosystem for years, thanks to its widespread adoption and support from companies like Oracle and MariaDB Corporation. Tools like phpMyAdmin have made the lives of web developers easier.

Today, however, PostgreSQL boasts an equally robust and rapidly growing ecosystem. Tools like pgAdmin provide a comprehensive management interface, while the DevOps world has embraced PostgreSQL thanks to native Kubernetes support, Helm Chart, specialized operators , and integrations with monitoring systems like Prometheus. Furthermore, the universe of extensions significantly expands the possibilities, making PostgreSQL a more dynamic and modular environment than MySQL.

PostgreSQL vs Oracle Database

One of the most interesting aspects of PostgreSQL's development is its ability to be perceived as a direct competitor to Oracle Database , a historic giant in the relational database industry. While MySQL and MariaDB have gained ground in the web world and in lighter applications, PostgreSQL has instead established itself as an enterprise alternative , suitable for replacing Oracle in numerous mission-critical scenarios.

Common advanced features

Many of Oracle's strengths are now found in PostgreSQL, thanks to constant evolution:

• Robust ACID transactions: Both platforms ensure consistency and reliability even in highly concurrent scenarios.
• Table partitioning: available in Oracle for a long time, now natively supported and optimized in PostgreSQL as well.
• Stored procedures and procedural languages: Oracle has always stood for PL/SQL, while PostgreSQL offers PL/pgSQL, a powerful and familiar language for those coming from the Oracle ecosystem.
• Granular permission control: both allow you to manage roles, privileges and security at the enterprise level.
• Advanced query optimizerPostgreSQL, like Oracle, is able to generate sophisticated execution plans and take full advantage of indexes and parallelism.

Where Oracle Stays Ahead

Oracle, with decades of development and an extremely broad ecosystem, maintains advantages in some particularly complex scenarios:

• Handling extreme loads at scale (data warehouse with petabytes of data).
• Integrated monitoring and tuning tools very advanced, part of the enterprise offering.
• Proprietary vertical features for specific sectors (e.g. banking or telecommunications applications).
• Official support with strict SLAs: being a commercial product, Oracle contractually guarantees service levels that are still indispensable for many companies.

Where PostgreSQL Stands Out

While Oracle maintains some areas of superiority, PostgreSQL has carved out an increasingly large niche for itself thanks to a number of practical advantages:

• Free licensePostgreSQL is free and open source. This dramatically reduces costs compared to expensive Oracle licenses.
• Extensibility: The ability to create custom data types and extensions makes PostgreSQL more flexible than Oracle in certain contexts.
• JSONB and hybrid dataPostgreSQL natively integrated NoSQL-like functionality, while Oracle introduced similar support later and less naturally.
• Global Community: In addition to commercial support from companies like EDB, PostgreSQL benefits from a large and collaborative community, which drives continuous innovation without proprietary constraints.
• Cloud AdoptionPostgreSQL is available as a managed service on all major providers (AWS, Azure, Google Cloud), while Oracle Cloud remains more niche.

Migrating from Oracle to PostgreSQL

In recent years, more and more companies have undertaken migration projects from Oracle to PostgreSQL . The main reasons are:

1. Cost reduction: abandoning Oracle licenses means saving millions of euros per year in large organizations.
2. Vendor independencePostgreSQL is not controlled by a single company, reducing the risk of lock-in.
3. Compatibility with PL/pgSQL: Similarity to PL/SQL simplifies the transition of applications and business logic.
4. Dedicated tools: there are toolkits like Now2Pg that facilitate schema and code conversion from Oracle to PostgreSQL.

Many organizations that have made this transition report that, once they have completed the migration process, PostgreSQL offers performance and reliability fully comparable to Oracle, with the advantage of open source flexibility.

License model

One of the aspects that has most favored the adoption of PostgreSQL is its licensing model . Unlike other DBMSs, PostgreSQL uses the PostgreSQL License , a very permissive open source license similar to the BSD license.

Main features of the PostgreSQL License

• Free use: Anyone can download, install, and use PostgreSQL without any licensing costs.
• Modification and redistribution: You can modify the source code and distribute customized versions of it, including in commercial products, without being required to release your changes to the public.
• Absence of copyleftUnlike licenses like the GPL, the PostgreSQL License does not require open source software. This makes it extremely attractive in corporate contexts, where internal customizations or extensions are often kept confidential.

In other words, PostgreSQL offers maximum freedom : you can use it for a personal project or for an enterprise solution distributed to thousands of customers, without ever having to pay royalties or worry about restrictions.

Comparison with MySQL/MariaDB (GPL)

MySQL (now owned by Oracle) and MariaDB primarily use the GPL (General Public License) . This is an open source license, but with a different philosophy than PostgreSQL:

• The GPL is a license Copyleft: If you distribute derivative software that incorporates GPL code, you are obligated to also release your source code under the same license.
• In practice, this means that to develop commercial applications based on MySQL, many companies prefer to subscribe to a dual license (typically the commercial one offered by Oracle for MySQL Enterprise), so as to avoid the constraints of the GPL.

This approach has often led to confusion and additional costs. PostgreSQL, however, with its permissive license, eliminates these issues at the root, making adoption simpler and more transparent.

Comparison with Oracle Database (commercial licenses)

The situation is completely different in the Oracle Database world . We're not talking about open source here: Oracle is a fully-fledged commercial product, with a licensing model based on annual or perpetual subscriptions , and is often very expensive.

• Oracle licenses are calculated based on the number of cores, users, or instances, and can easily reach millions of euros for large organizations.
• Added to these are the costs of maintenance and support, which in many cases are required to receive updates and security patches.
• Furthermore, the Oracle ecosystem is highly closed: there is no freedom to modify the code or create custom variants.

In this scenario, PostgreSQL represents a revolutionary alternative: it offers many of the same advanced features as Oracle, but with a license that is not only free, but also allows for maximum autonomy.

A strategic competitive advantage

For many companies, the PostgreSQL license has become a competitive advantage :

• allows you to drastically reduce costs,
• eliminates the risk of vendor lock-in,
• It allows you to develop customized solutions without sharing obligations.

These elements have meant that PostgreSQL has been chosen not only by startups and independent developers, but also by banks, government agencies and multinationals , who have seen its license as an opportunity for long-term strategic adoption.

The concrete advantages of PostgreSQL

At this point, it's clear why PostgreSQL is considered by many to be the most solid choice among open source DBMSs. But what are the concrete advantages that really make a difference in the daily life of a developer or system administrator?

1. SQL Standards Compliance

For those coming from MySQL, PostgreSQL may initially seem more "rigid": it doesn't tolerate incorrect queries and requires strict adherence to SQL syntax. This rigor, however, translates into greater code consistency and portability . If you were to move your applications to another standards-compliant RDBMS in the future, you'd encounter fewer problems. In complex scenarios, this adherence reduces the risk of silent bugs and unexpected behavior.

2. Rich in out-of-the-box features

PostgreSQL natively offers tools that MySQL/MariaDB often requires workarounds or third-party plugins. Practical examples:

• With PostgreSQL you can use window functions to calculate moving averages, rankings, or cumulative percentages in a single query.
• You can take advantage of Recursive CTEs to navigate hierarchical structures such as categories, family trees, or navigation menus.
• You can create materialized views to optimize heavy queries, which in MySQL requires manual solutions.

All of this is integrated and mature, with no need for external patches or extensions.

3. Advanced Concurrency Management (MVCC)

Anyone who has managed high-traffic applications on MySQL knows what it's like to encounter heavy locks that slow down the entire system. PostgreSQL, thanks to its MVCC model, allows thousands of transactions to coexist without significant blocking, offering natural scalability in multi-user environments . For an e-commerce or SaaS platform with thousands of customers, this feature makes the difference between a smooth system and one that crashes under load.

4. Advanced data types and JSONB

PostgreSQL goes beyond typical numeric and text columns. It natively supports arrays, ranges, UUIDs , and most importantly, JSONB , a binary representation of JSON that allows for efficient searching and indexing. This means you can have traditional relational and semi-structured data in the same database, without having to rely on a separate NoSQL database. For example:

• You can save product sheets in JSON format while maintaining classic relationships with categories and orders.
• You can index nested attributes in JSONB documents and query them with high performance.

For those accustomed to MySQL, where JSON is supported but with limitations, this is a real revolution.

5. Partitioning and parallel queries

PostgreSQL handles partitioning natively and is increasingly optimized. This allows you to distribute huge tables across multiple partitions and dramatically improve performance. At the same time, support for parallel queries allows you to fully utilize multi-core servers: a single query can be broken down and processed in parallel, reducing response times even on huge datasets.

6. An extensible and modular ecosystem

PostgreSQL isn't just a database: it's an extensible platform . Thanks to extensions, you can transform it into a GIS (with PostGIS), a time-series database (with TimescaleDB), or a distributed system (with Citus). In practice, you're not limited to what the core offers: you can build a "custom" database for your project, something that's much more limited with MySQL/MariaDB.

7. Permissive license and total freedom

From a legal and commercial perspective, PostgreSQL offers a huge advantage: its permissive license frees you from copyleft restrictions and licensing fees. You can integrate PostgreSQL into a proprietary product, redistribute it, and modify it, without ever having to share the source code. This makes it ideal not only for startups, but also for large companies that need to ensure legal compliance and save money.

8. Cloud and DevOps support

PostgreSQL is now the de facto standard in the cloud . It's available as a managed service on AWS, Azure, and Google Cloud, and is natively supported by DevOps tools like Kubernetes, Helm, and Terraform. This means you can launch a PostgreSQL cluster in minutes, confident that your stack will be compliant with modern best practices.

PostgreSQL as a platform

One of the qualities that most distinguishes PostgreSQL from other open source DBMSs is its nature as an extensible platform . It is not just a relational database, but a true modular ecosystem , which can be adapted to very different scenarios thanks to the extension system.

This philosophy has made PostgreSQL a “Swiss Army Knife” for data: the same engine can be used for traditional web applications, geographic systems, time series management, or even as a large-scale distributed database.

Let's see some emblematic examples.

PostGIS: PostgreSQL for geographic data

PostGIS is probably the most famous and widely used extension. It transforms PostgreSQL into a geographic reference database (GIS) , capable of managing spatial data with pinpoint precision.

With PostGIS you can:

• Save complex geometry such as points, lines, and polygons.
• Perform spatial queries (e.g., “find all restaurants within 2 km of this location”).
• Perform advanced geographic operations such as area intersection, distance between GPS coordinates, or map projection.

It's no coincidence that PostGIS is the de facto standard for government agencies, mapping platforms, logistics applications, and environmental projects. A concrete example: most applications that use OpenStreetMap data rely on PostgreSQL with PostGIS.

Citus: PostgreSQL as a distributed database

If the challenge is horizontal scalability , Citus comes into play . This extension allows you to transform PostgreSQL into a distributed database , capable of dividing data across multiple nodes (sharding) and managing large-scale parallel queries.

With Citus:

• You can distribute huge datasets across multiple servers without changing your application architecture.
• SQL queries are automatically parallelized and aggregated by nodes.
• You get a database that grows “as your business grows,” without the typical limitations of a single node.

Citus is particularly popular with those developing SaaS applications or platforms with millions of users, because it allows you to scale without having to abandon PostgreSQL or rewrite the database logic.

TimescaleDB: PostgreSQL for Time Series

Another example of how PostgreSQL has become a multipurpose platform is TimescaleDB , an extension designed for time series management.

Time series are essential in scenarios such as:

• IT systems performance monitoring,
• IoT metrics collection,
• real-time financial data analysis,
• industrial sensor management.

TimescaleDB leverages the PostgreSQL engine to offer features typical of time-series databases: data compression, time-range-optimized queries, and automatic retention. Unlike specialized databases like InfluxDB, however, it retains the full power of SQL and integration with the PostgreSQL ecosystem.

Other extensions and use cases

In addition to PostGIS, Citus, and TimescaleDB, the PostgreSQL ecosystem offers a huge range of extensions:

• PgRouting, for calculating routes on road networks or graphs.
• pg_partman, for advanced partitioning management.
• PLV8, which allows you to write functions directly in JavaScript.
• pg_stat_statements, essential for monitoring and optimizing queries.

This modularity makes PostgreSQL a universal platform : you're not tied to a fixed model, but can customize it as needed. In this respect, PostgreSQL surpasses both MySQL (which has a more limited ecosystem) and many commercial databases, which tie functionality to expensive licenses.

PostgreSQL as the “backbone” of modern data ecosystems

Ultimately, the ability to extend PostgreSQL has transformed it from a “simple RDBMS” to a foundation layer for modern applications . Instead of building a NoSQL database, a GIS database, and a time-series database, many companies choose to build everything on PostgreSQL, centralizing data and simplifying the infrastructure.

This approach not only reduces management costs, but also improves consistency and security, because all data—relational, geographic, temporal, or distributed—coexists in the same ecosystem, with the same transaction, backup, and permission logic.

Conclusion

The story of PostgreSQL is an extraordinary example of how a project born in the academic world, initially conceived as an experiment to overcome the limitations of the first RDBMS, has managed to transform itself into one of the most solid and respected technologies in the enterprise world.

Today, in 2025, PostgreSQL is no longer just an "alternative database" to MySQL or MariaDB. It is a benchmark in the data management system landscape, capable of combining:

• la relational solidity of a classic RDBMS,
• la NoSQL-like flexibility thanks to JSONB,
• la distributed scalability via extensions like Citus,
• la analytical power ensured by window functions, materialized views and CTE,
• , modular versatility offered by an ecosystem of extensions that makes it a platform in its own right.

For those coming from the MySQL world, PostgreSQL may initially seem more rigorous and less permissive. But it's precisely this consistency that makes it the best choice for projects that need to last over time, avoid ambiguity, and guarantee consistent performance even in complex scenarios. Where MySQL focused on simplicity, PostgreSQL has invested in robustness and standards adherence.

For those looking at Oracle Database, PostgreSQL represents a cultural and economic revolution : not only a drastic reduction in licensing costs, but also the freedom to build a data infrastructure without proprietary constraints. Sure, Oracle remains unbeatable in some ultra-specialized contexts, but for the vast majority of business applications, PostgreSQL offers everything you need, with the added benefit of a vibrant community and an open ecosystem.

From a licensing perspective, its permissive open source nature makes it even more attractive: PostgreSQL can be adopted without legal concerns, hidden costs, or the risk of vendor lock-in. This freedom is one of the reasons we see it everywhere, from the cloud to banks, from e-commerce systems to IoT applications.

Looking to the future, PostgreSQL's trajectory is clear: every year it adds new features, strengthens its position in the managed services of major cloud providers, and increasingly becomes a point of convergence for developers, businesses, and public administrations. It's not just a simple DBMS; it's a universal data platform , capable of adapting to any scenario.

Ultimately, PostgreSQL is much more than an alternative to MySQL or Oracle: it is proof that open source, when supported by an active community and a healthy development model, can compete on equal terms with the commercial giants and, in many cases, surpass them.

For developers and system administrators today who are evaluating which database to adopt, the answer is clear: PostgreSQL is a secure, modern and strategic choice , suitable for those who want to build solid and scalable applications, with the certainty of being able to grow without constraints and without prohibitive costs.