PostgreSQL has been widely adopted by the industry in recent years. Some of the top companies in the world are using PostgreSQL.

Here is a tiny list of really big names running PostgreSQL databases:

 

Goldman Sachs Logo  Bloomberg Logo  UN Emblem Logo   Nokia Logo   BMW Logo

 

Thousands of companies out there have PostgreSQL for countless business critical and non-critical applications.

PostgreSQL is not just used in one industry – it is pretty much everywhere. From automotive to water management. From archaeology to weather services. PostgreSQL is everywhere these days and the number of deployment is growing all over the world.

The following listing shows a couple of examples of how PostgreSQL is or can be used in the real world.

Use case 1: Financial industry

PostgreSQL is highly suitable for the financial industry. PostgreSQL is fully ACID compliant and therefore ideal for OLTP (Online Transaction Processing) workloads. However, PostgreSQL is not only a good choice for its superior OLTP capabilities – it is also a highly capable analytical database and can be integrated nicely with mathematical software such as Matlab and R.

PostgreSQL can be used for a variety of tasks and operations.

OLTP, analytics, and business intelligence

Use case 2: Government GIS data

PostgreSQL is not only a tool for the financial industry – there is also a really powerful GIS extension called “PostGIS” which provides hundreds of functions to process geometric data in various formats. PostGIS is highly standard compliant and is one of the de-facto standards in the Open Source GIS world.

In combination with QGIS or GeoServer the Open Source community provides powerful means to handle geodata. Check out website on PostGIS to find out more about our geodata services.

PostGIS for spatial data

Use case 3: Manufacturing

Many world class industrial manufacturers use PostgreSQL to speed up innovation and to drive growth boost through customer-centric processes, and optimize supply chain performance using PostgreSQL as a storage backend. PostgreSQL is a reliable, long term data stores and offers you reliable storage at low costs.

In industrial manufacturing reliability is everything. If a production site is down due to a failure it can easily cost millions. Therefore PostgreSQL is the ideal choice because it can be configured for automatic failover, full redundancy, and almost zero downtime upgrades.

PostgreSQL has gained a lot of momentum in manufacturing recently because Oracle has changed its license policy in a way that it has become hard for many companies to sustain high license costs.

Automatic failover and zero downtime upgrades

Use case 4: Web technology and NoSQL workloads

Modern websites might require thousands or even hundreds of thousands of requests per second to serve your customers. Scalability can be a major issue and the PostgreSQL community has worked hard to address those scalability questions in the past couple of years.

PostgreSQL works fine with all modern web frameworks including but not limited to: Django (Python), node.js (JavaScript), Hibernate (Java), Ruby on rails, PHP, and a lot more. Due to PostgreSQL’s replication capabilities, websites can easily be scaled out to as many database servers as you need.

PostgreSQL is not just a relational database – it can also serve as a NoSQL-style data store. There is no need to choose between the relational and the document oriented world. You can have both in a single product.

Scalable NoSQL workloads with PostgreSQL

Use case 5: Scientific data

Research and scientific projects can generate terabytes of data, which have to be handled in the most beneficial and most efficient way possible. PostgreSQL has wonderful analytical capabilities and offers a powerful SQL engine, which makes processing large amounts of data a real joy.

On top of that PostgreSQL can easily be extended. You can write your own aggregation functions and you can come up with your own business logic in the database. By bringing the algorithms close to your data, a lot more efficiency can be achieved than by performing all operations on the application level.

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