In the database industry, PostgreSQL and SQL Server have solid reputations. SQL Server is preferred by many organizations, especially those companies highly integrated with Microsoft, understandably because of the smooth integration. On the other hand, PostgreSQL attracts companies that are attracted to the flexibility and strength that the open-source solution offers.

So, how do you decide which one best suits your company? This article will try to answer that question by comparing the strengths of both database systems to key business factors, and answer the question: does migration from SQL Server to PostgreSQL worth it? Let’s begin!

PostgreSQL vs. SQL Server: Head-to-Head Comparison

Cutting short, how does PostgreSQL differ from SQL Server? We’ll mention some relevant differences to help you select the one that suits your needs.

Where Can You Run Them?

PostgreSQL is open source and, therefore, very flexible. This software runs on a variety of operating systems, including Linux, macOS, Windows, and others. It also runs in modern environments such as Docker containers and Kubernetes clusters.

If SQL Server can be said to offer anything, it is limited in its reach. Supported mainly by Microsoft Windows, it recently includes support for the Linux platform among its newer features.

Architectural Approaches

PostgreSQL is a brilliant open-source database. The most striking thing that distinguishes this database from others is that it uses the PL/pgSQL programming language. This is an excellent programming extension to basic SQL commands as it provides features such as user-defined data types, custom module implementations, seamless integration of today’s data through JSON, and advanced trigger options so that your actions can be automated according to events occurring in the database.

Architecturally, however, PostgreSQL takes a very interesting approach. Each database runs in an independent process in the operating system, giving the user a really high degree of isolation and making it easier to manage and monitor them individually. However, sometimes, an isolated nature makes scaling multiple databases much more difficult.

SQL Server, however, handles T-SQL, which extends standard SQL and packs a wealth of features into it. It allows users to manipulate data more thoroughly, process complex strings, and implement procedural logic within the database.

A buffer pool is the architecture of SQL Server under which all its components revolve. It is a designated area of memory that stores frequently accessed data. The size of this pool can be made variable and hence adjusted according to the users’ performance requirements. High availability and disaster recovery are other notable features of SQL Server, which allow replications of a database over multiple instances seamlessly to improve resilience.

SQL and Beyond

PL/pgSQL is a procedural language that greatly enhances the user experience in PostgreSQL. In addition to the standard SQL features, PostgreSQL supports user-customizable data types, user-defined modules, and seamless integration with JSON data. It has been further extended to provide advanced trigger options to automate complex database actions.

T-SQL is another extension of SQL Server, just like SQL itself. It is intended for very efficient data manipulation, string processing, and procedural programming within an environment where SQL Server mostly exists. Thus, a user is provided with more sophisticated tools to manage and work with his data.

Working with Tables

PostgreSQL has this excellent feature known as “temporary tables.” These are similar to temporary storage spaces within the database for storing results intermediate to complex logic and procedures, making things easier and faster by removing clutter.

In SQL Server, a schema is the “container” that helps organize tables. Schemas can be defined as folders that contain a specified number of tables. They also enforce security boundaries: a particular user can access some but not all tables. A property or part that is much thought about and defined when designing a table includes the type of data it will contain and the acceptable ranges, thus keeping the stored data accurate and well-structured.

Indexes: Finding Data Faster

Indexes are similar to shortcut paths in your database; instead of searching each and every row, indexing helps you locate the information you need quickly.

There are a lot of indexes offered in PostgreSQL which are specially designed for different scenarios. An example of some of the indexes includes the B-tree indexes, which behave like the old-fashioned library card catalog. The hash indexes can be used where a speedier retrieval is desired. Besides this, some indexes are for specific types of data. PostgreSQL allows the user to build indexes from complex expressions or just portions of tables, thereby giving a user the power to compute how the data will be indexed.

The SQL Server approach to indexes is different from that. It mainly relies on two types of indexes: clustered and non-clustered. A clustered index is like arranging books on a shelf depending on the author. It defines how the physical order of data is within the table itself; there can only be one clustered index per table. Examples of non-clustered indexes are those that create an index outside the table and then refer to the appropriate data in the table according to the key values stored within.

SQL Server automatically creates indexes while you define primary keys or unique constraints. This keeps the data consistent and ensures you can find your information quickly.

Scalability

PostgreSQL is a good bet when the need arises to scale. It automatically handles increasing workloads with minimal disturbance, with its ability to exploit several CPU cores working simultaneously. This way, it divides complex tasks and completes them in parallel, thus significantly increasing speed.

Scaling PostgreSQL involves distributing the workload across multiple servers. Installing standby servers that serve all read requests improves performance and ensures high availability. Sharding is another option: it divides your data across multiple servers, making managing and scaling much easier.

SQL Server also allows the use of multiple CPU cores, although its extent of scalability depends on the edition. In the standard edition, most of this use is limited, while the enterprise edition offers maximized flexibility. A central feature in SQL Server is “hyper-scale,” which allows dynamic adjustment of resources allocated to your database with respect to current needs. This flexibility is vital to companies with fluctuating data demand.

Performance

PostgreSQL regularly outperforms SQL Server in many aspects. For example, PostgreSQL’s partitioning features are very robust and free of charge. They involve breaking large tables into small, manageable chunks, thus optimizing query performance.

PostgreSQL is also very good at concurrency: different users can read and write data with minimum interference in one another’s actions. This minimizes the probability of deadlocks, which occur when two or more users try to access and modify the same data at the same time.

SQL Server could not yet be improved and gets better but circumvented by concurrency, sometimes causing slowdowns.

Choosing Between PostgreSQL and SQL Server

Both PostgreSQL and SQL Server have their good sides. So, which is the better choice? After some deliberation, PostgreSQL has nearly always been the better option. Not only is PostgreSQL free and open-source, but it also offers a wide range of features that are readily available and easy to use, unlike some of the features in Microsoft SQL Server.

Perhaps PostgreSQL’s top feature is its ability to multitask with few delays. This is much needed in today’s high-paced world, where multi-threading is expected with so much happening at once in a database.

If you’re a small business, PostgreSQL could be an excellent choice. It’s free, offers robust features, and can be easily installed on various operating systems. However, if your business is heavily integrated with the Microsoft ecosystem, SQL Server might still be the most suitable option due to its seamless integration with other Microsoft products.

Considering a Database Migration?

If you plan to migrate from one database to another, such as from SQL Server to PostgreSQL, consider using an automated migration tool. Compared to manual migration, this can significantly speed up the process and reduce the risk of errors.

Ispirer Toolkit is a powerful tool that supports migrations to and from over 40 databases, including PostgreSQL and SQL Server.