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Solving Concurrency With PostgreSQL

Databases are an organized way for enterprises to store and use their data. Since most of the data used in an organizational structure are related or interlinked, relational database solutions have been an accepted form of data management for a long time.
A Relational Database Management System (RDBMS) is a system that allows an organization to manage and administer its relational database.
One of the problems that Relational Database Management Systems are solving is concurrency. Usually a developer wants the application to be able to serve multiple users at the same time without going offline for either maintenance or for reconciliation of daily transactional activities in the support system.
Users want to have access to their records and analytical system and see up-to-date records, as to what just happened an instant ago. In the dawn of online and contact-less payment systems and what not, users want to be able to see the bank activities as they happen. In response to this scenario, developers have to give users this experience and let them have everything at their finger tips by providing dashboards that show data that updates in real real-time by sending confirmation text messages immediate the user makes a payment.
The issue will then be how can a developer build such a system that knows how to implement such features? This is where PostgreSQL comes in.
PostgreSQL is the world's most advanced open source relational database, and as a Relational Database Management System (RDBMS), PostgreSQL can handle concurrency and diverse workloads. PostgreSQL can be used to implement transactional system of records and at the same time deliver data analytics.
To be able to achieve the implementation of these activities on top of the same technology, the manager or developer needs a way to express simple transactions and complex analytics aswel. Here is where the developer needs a Structured Query Language (SQL). The Transaction Control Language part of SQL allows the developer to implement concurrency in the application.
With SQL, the developer can easily implement the CRUD operations. CRUD stands for Create, Read, Update, and Delete.
With SQL, a single statement can take care of a number of rows at the same. This is because SQL is excellent at batching operations. The CRUD operations of the application covers the system of records aspect of the activities and other adminstrative use-cases like creating users, groups, and data organization.
It must be mentioned, though, that some activities are had to implement with SQL. But with Postgres, we access to several extensions that gives us the power to process data right from the database.In distributed systems, the computation can be sent whether data is already, or send the data to the computation nodes.
The beauty of Postgres is that it gives the developer power to choose either to retrieve the data and then process it in the application nodes or choose to process the data right where it is, in the database.
In conclusion, in order to effect concurrency in your application, that is versatile in terms of architecture (CRUD, System of Records, Analyticand Dashboards), and that is powerful in terms of computation, Postgres is the answer. So, if you're not sure with what transactional system to use, and when scaling your application to impossible volumes, try Postgres.

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