Ideally speaking, the database system must come with advanced compression technique out of the box.

The scalability feature of a database system is directly dependent on the ability of compression of the data. Due to the lack of proper indexing implementation is SQL server, they have omitted one of the most used variable system called array. Not only that, PostgreSQL has modules or extensions support and you can do a lot of things that SQL server is incapable of. Moving on, PostgreSQL has indexable functions feature will boost the performance of the database to another level. PostgreSQL releases updated version regularly and they keep up with the trend for offering faster performance. In such a scenario, SQL Server’s approach of releasing a new version after a few years is outdated. Indexing – The technologies are updating faster than ever. As for SQL Server, there is a proper partitioning feature but you have to buy the feature as an add-on whereas, in PostgreSQL, you get it for a lesser price and with more efficiency. As the application scales higher, the database will become large and if it is not split, it can become larger and accessing data will take a lot of time. Partitioning is also important from the scalability point of view. This helps in faster performance when it comes to accessing the data from the fractions rather than going through the entire large table. As a database size and especially table size grows, it is important to go for partitioning. Partitioning is the process by which large tables are divided into smaller fractions.

Partitioning – Just like concurrency, partitioning is a big feature of the database system. In this comparison, PostgreSQL has a better concurrency management system and there is less chance of deadlock situations due to its optimization MVCC feature. This causes mismanagement of data and the processes of the applications get very slow. SQL Server has underdeveloped concurrency and you are sure to get various locked, blocked, and deadlocked reports in the log. In every application, certain data are shared by various concurrent processes running and the robust this concurrency of data can be, the faster and flawless will be the performance of the database as well as the application. Concurrency refers to the feature by which multiple processes can access and modify shared data at the same time. Today, let us compare the performance and scalability factors of two most popular database systems MS SQL Server and PostgreSQL.Ĭoncurrency – Concurrency is a big factor in determining the performance of a database system. If the database system you have for your application does not provide a robust scalability feature and if the performance takes a beating as the load increases, the application’s popularity will take a hit. Not only that, every application gets modified for better user experience and introducing new features and the requirements for database storage increases considerably. There are many instances where the developers have to migrate from one database system to another just to boost the performance and speed of operation in database-heavy applications. The performance and scalability of the database system can affect any project in a significant way.

Postgresql vs sql server tutorial