Postgres has some amazing features like it has introduced a pg vector. Which am using mostly everywhere in my AI applications. It comes handy I don't have to setup two different databases for relational and vector seperate, both of them postgres provides, it saves my headache. Review collected by and hosted on G2.com.

Nothing much but postgres do not have an ability to store the data entirely in ram for fast access which Mysql like database provides Review collected by and hosted on G2.com.

I use PostgreSQL as the core database for a Pet Clinic Management System I built. It supports multi-role authentication (admin, doctor, staff, and pet owners), appointment scheduling, medical records, vaccination tracking, and invoice management, all within a single relational schema.

What I value most is PostgreSQL’s ability to enforce complex relational integrity. In my system, the appointments table includes foreign key constraints that link to animals, owners, doctors, schedules, and staff at the same time. PostgreSQL handles cascading deletes and referential integrity smoothly—for instance, when an owner is deleted, their associated animals and related records are automatically removed.

I also like the strong support for enum types, sensible timestamp defaults, and multi-column unique constraints, such as preventing duplicate owner registrations. These features made my schema design cleaner and more dependable. On the application side, PostgreSQL integrates well with PHP via PDO, so parameterized queries are easy to write and help keep the system secure against SQL injection. Review collected by and hosted on G2.com.

Initial setup and configuration—especially when it comes to user roles, privileges, and connection pooling—feels more involved than with simpler databases. In my case, for a pet clinic system I run locally using XAMPP/MariaDB syntax, migrating the schema to PostgreSQL took extra care because of syntax differences (for example, AUTO_INCREMENT vs. SERIAL and how enums are handled).

On top of that, debugging complex multi-join queries—such as joining appointments with animals, owners, doctors, and schedules—can lead to error messages that are difficult to interpret, particularly for developers coming from a MySQL/MariaDB background. Review collected by and hosted on G2.com.

What I like most about PostgresSQL is it's reliability, performance and rich feature set. We use it for production workflows, and it has handled everything from transactional data to large partitioned tables effectively. Features such as indexing, query optimization, EXPLAIN ANALYZE make it easy to diagnose and improve performance issues. Review collected by and hosted on G2.com.

One drawback of PostgresSQL is that advanced administration and performance tuning can have a steep learning curve. As the database grows, tasks such as partitioning, indexing strategy, query optimization require experienced database knowledge. While PostgresSQL performs very well, troubleshooting complex queries can take significant effort compared to some managed database solutions. Review collected by and hosted on G2.com.

PostgreSQL offers robust database functionality that covers a wide variety of use cases. The ability to run this database locally for testing and development as well as in the cloud is imperative for ensuring that software runs as expected when it goes into production. The adoption of PostgreSQL by a wide variety of cloud providers has made this a great option for most software projects. Review collected by and hosted on G2.com.

I have few complaints about PostgreSQL, it is one of the most versatile and performant databases that I've used Review collected by and hosted on G2.com.

What I like best about PostgreSQL is how it combines power, reliability, and flexibility in one platform. Its SQL standards compliance, strong performance, advanced indexing, and support for both relational and JSON workloads make it suitable for everything from transactional apps to analytics platforms. From a UI/UX standpoint, it works well with excellent tools like pgAdmin and many third-party clients. In terms of integrations, it connects easily with BI tools, ETL pipelines, cloud platforms, and programming languages. For pricing / ROI, being open-source significantly lowers total cost while still delivering enterprise-grade capabilities. It also has a large community for support / onboarding, with abundant documentation and tutorials. On AI / Intelligence, its growing ecosystem for vector extensions and ML integrations makes it increasingly relevant for modern AI-driven applications.ern AI-driven applications. Review collected by and hosted on G2.com.

What I dislike about PostgreSQL is that while it is powerful, it can feel complex for new users. The UI / UX depends heavily on third-party tools rather than a polished native interface. In terms of performance, it may require careful tuning for very high write-volume workloads or large-scale horizontal scaling. Some integrations and enterprise features can need extra setup compared with fully managed commercial platforms. For support / onboarding, community resources are strong, but official hands-on vendor support is limited unless using a managed provider. On AI / Intelligence, capabilities often rely on extensions rather than built-in native features. Review collected by and hosted on G2.com.

PostgreSQL's robust access control and row-level security make it an excellent choice for storing sensitive security data. Its reliability, ACID compliance, and extensive audit logging capabilities are critical when handling threat intelligence, incident records, or compliance data. The open-source nature means no vendor lock-in, and the active community ensures rapid security patches and updates Review collected by and hosted on G2.com.

PostgreSQL's initial configuration can be a security risk if not hardened properly out of the box — default settings are not always production-ready from a security standpoint. Managing encryption at rest requires additional setup and third-party tooling, unlike some commercial databases that offer built-in encryption solutions. Review collected by and hosted on G2.com.

What I like most about PostgreSQL is its reliability, performance, and flexibility. It supports advanced SQL features, handles complex queries efficiently, and offers powerful capabilities like JSON support, window functions, CTEs, and extensions. I also appreciate that it's open source, has a strong community, and integrates well with modern data engineering and analytics tools. Review collected by and hosted on G2.com.

One common complaint is that PostgreSQL may require more manual performance tuning as databases grow, especially around autovacuum and indexing. Another is that horizontal scaling can be more challenging compared to some distributed database systems. Review collected by and hosted on G2.com.

We use PostgreSQL as the sole choice for practically every new service that we launch, and as a software engineer in a medium sized company, we'd love to do more but cannot do it. I'm most impressed by how reliable it is, and how much more it has to offer than standard SQL. The JSONB support is a godsend to us, because it allows us to have the flexibility of a NoSQL data model to our semi-structured data, without losing our strict ACID requirements of our transactional data. The extension ecosystem is also phenomenal. We can typically select an extension to easily incorporate geospatial functionality into PostGIS or time-series data into its time-series management utility, without having to try out a whole new database technology. It can easily process complex queries and concurrency heavy read and write without breaking a sweat and is open-source, so we are not faced with the licensing problems found with enterprise alternatives to it. Review collected by and hosted on G2.com.

It's a great database, but it has its oddities. Managing connections has always been the most cumbersome task that irritates our staff. PostgreSQL runs a process for every connection, so if you're running a lot of microservices trying to connect to it in a short period, you can easily end up consuming a lot of memory. Although we had to come up with PgBouncer early on to deal with connection pooling, I hope that good connection pooling is integrated into the core system from the start. The other small complaint is about the autovacuum. With our very write-intensive tables, optimizing the auto-vacuum settings to not cause table bloating yet still maintain query performance was quite the process of trial, error, and mastering the documentation. When you begin scaling up, it will need a bit more hands-on knowledge of database administration than some of the managed, cloud-native databases. Review collected by and hosted on G2.com.

What I like most about PostgreSQL is the balance it achieves between robustness and flexibility. It offers reliable ACID transactions, strong referential integrity, and a powerful query optimizer. Additionally, it supports JSONB, advanced indexes, and extensions, allowing the combination of the relational model with semi-structured cases without the need to change engines. Overall, I find it a stable, scalable, and suitable option for both small projects and critical systems. Review collected by and hosted on G2.com.

PostgreSQL may require more careful initial configuration and optimization compared to simpler databases. In teams without experience in tuning, indexes, and query planning, performance can degrade if the schema is not designed correctly from the start. Additionally, some advanced administrative tasks demand a deeper technical knowledge. Review collected by and hosted on G2.com.

PostgreSQL offers strong performance, reliability, and advanced SQL capabilities. Features like JSONB support, indexing options, window functions, and extensions make it highly flexible for both transactional and analytical workloads. It integrates well with modern stacks and handles large datasets efficiently while maintaining data integrity. Review collected by and hosted on G2.com.

Initial configuration and tuning can be complex, especially for high-traffic systems. Some administrative tasks require deeper database knowledge, and horizontal scaling is not as straightforward compared to certain distributed databases. Review collected by and hosted on G2.com.