PostgreSQL Vs SQL Server: 16 Critical differences

For a long time, Microsoft SQL Server has been an ideal choice for businesses which depend on other Microsoft products, but PostgreSQL has taken strides to rise to the top of its class not just because of the benefits of going open-source but also for its active user base and useful features.

This brings the discussion to a close. Comparison of PostgreSQL with SQL Server will help you better understand the possible advantages and trade-offs between the two platforms, and which one is better suited for your purpose.

Let's dig in!

What exactly is PostgreSQL?

In addition to being completely open and free, PostgreSQL is also highly adaptable. You can, for instance, develop custom functions, determine the types of data you store, and even code in several programming languages, without having to rebuild your database!

History

This is a quick overview of PostgreSQL throughout the times:

• Ingres was first developed in the year 1977.
• Michael Stonebraker and his associates were the first to develop Postgres in 1986.
• In the year 1990, support for PL/ pgSQL and ACID conformance was added to PostgreSQL.
• NYCPUG (New York City PostgreSQL User Group) joined the PgUS (United States PostgreSQL Association) at the time of 2013.
• In 2014, the PGconf marked the beginning of a new era that was a new era for PostgreSQL users.

Main Features

We'll now move on to take a look at the features of PostgreSQL that make it an indispensable tool in the marketplace.

• Standards compliance and reliability: PostgreSQL's write-ahead logging lets it be distinguished as a fault-tolerant database. PostgreSQL is also ACID compliant and provides full support for views, foreign keys, triggers, joins, and stored procedures, in various languages. It supports the majority of SQL Data Types 2008, including BOOLEAN, NUMERIC, INTEGER DATE VARCHAR, TIMESTAMP, INTERVAL as well as CHAR.
• Strong extensions: PostgreSQL has robust features such as point-in time recovery, multi-version concurrency (MVCC), tablespaces, granular access controls, and online/hot backups. PostgreSQL has also been designed to be locale-aware, allowing case-sensitive sorting, case sensitivity and formatting. It's extremely scalable with regard to the volume of data it can manage and the amount of simultaneous users that can be accommodated.
• Open-source license: You are able to access the PostgreSQL source code under an open-source license. This gives you the liberty to modify the code, apply it, and use the code however you like free of charge. In addition, PostgreSQL incurs no licensing fee, which takes care from the potential risk of over-deploying. The PostgreSQL community of users and contributors are constantly finding fixes and issues, which contribute to the overall security of the database system.

Use Cases

PostgreSQL's versatility allows it to be leveraged to be used in many different use cases like:

• Federated hub database PostgreSQL's JSON support as well as foreign data wrappers permit it to link with other storage systems -- like NoSQL data types as well as serve as a federated hub to databases that are polyglot.
• General-purpose OLTP Database: Large enterprises and startups both utilize PostgreSQL as their primary storage for their internet-scale applications, products, and solutions.
• Geospatial Database: PostgreSQL supports geographic objects when used with its PostGIS extension. It also functions as a geospatial data store in conjunction with geographic information systems (GIS) and other services that are based on location.
• LAPP stack that is open source: PostgreSQL is also able to be used to run dynamic applications and websites as part of an incredibly robust alternative to the LAMP stack. LAPP stands for Linux, Apache, PostgreSQL, Perl, PHP, and Python.

What Is SQL Server?

SQL Server was designed by Microsoft as a relational data management system that boasts many years of experience, 32 years to be exact. Microsoft SQL Server is considered a software product with its primary function being collecting and retrieving data demanded by different software applications.

These applications might either run on a different machine within networks or even on the same computer. Microsoft SQL Server has seen a lot of updates over time, and has evolved into one of the top maintained and most popular RDBMSs on the market.

SQL Server owes a large part of its success to the company that created it, Microsoft. At the time MS SQL Server was in its infancy, Microsoft had already established itself as a technology giant.

SQL Server has managed to create a name for itself as a management of databases by offering a wide array of tools and applications to make data management easier. The extensive GUI (GUI) allows intuitive and effortless work with database, while also allowing you to create statistics to support your report.

History

Here is a brief overview of Microsoft SQL Server over the years:

• The development of SQL Server began in 1988 when Microsoft collaborated in partnership with Sybase along with Ashton-Tate to develop the software for maintaining and creating databases which would give a boost to Microsoft's business database market.
• SQL Server 1.0 was rolled out in 1989. It was the first version to use the facility of system administrators (SAF) to build databases. The documentation was not available however it was able to allow users to use SQL queries and define parameters. The initial code sample that was written for Microsoft SQL Server was penned by Sybase.
• As time went by, more recent versions of SQL Server were made available with more upgrades and additional features. SQL Server 2019, or Aries is the latest update to the list of extensive versions, focusing on making database functions even more intuitive to use. It includes large data cluster options, giving users the ability to work on massive databases.

Main Features

Enough history talk. Let's look at a couple of pivotal aspects that make SQL Server such a wonderful catch:

• Robust security platform: SQL Server allows the protection of your information in motion as well as at rest , with features built in to protect data as well as data classification as well as alerts and monitoring. Through SQL Server, you can securely encrypt sensitive information and make complex computations with encrypted data. You can also allow the data to be accessed by role, complete with complex row-based filtering.
• Performance that is industry-leading: SQL Server boasts record-breaking speed on Linux as well as Windows because it always leads over TPC-H's data warehousing workload, TPC E OLTP workload and performance of real-world applications test results. It is also possible to use the in-memory capabilities of SQL Server's database like memory-optimized tempdb as well as persistent memory support. This can improve the performance of your critical workloads.
• Intelligence across your information with large data clusters: SQL Server allows you to gain valuable insights through all of your data querying data across your entire array of data sources including Azure SQL Database SQL Server, Teradata, MongoDB, Azure Cosmos DB as well as many others -- and all without the need to move or replicate data. It is possible to create the shared lake of data by combining both unstructured and structured data in SQL Server and then accessing the information either via Spark or the T-SQL.

Use Cases

SQL Server's extensibility and performance allow it to be leveraged to benefit from a wide range of use cases like:

• Replication service: SQL Server replication services are utilized by SQL Server to harmonize and replicate database objects either in a subset of objects present or as a whole. Replication services follow the subscriber/publisher model i.e. the changes are transmitted via a single database server (publisher) and are collected by other databases (subscribers).
• Notification Services: Notification services were first released as an after-release upgrade to SQL Server 2000. This is a method of making data-driven changes and then sending them to the notification services subscribers.
• Machine learning services: SQL Server machine learning capabilities are available within SQL Server. SQL Server instance, letting individuals perform data analysis and machine learning without having transfer data over the network or be hindered by the memory of their personal computers.
• Analysis Services SQL Server analysis services (SSAS) adds the ability to mine data and use OLAP to SQL Server databases. The OLAP engine provides support for the relational online analysis processing (ROLAP) as well as multidimensional online analytic processing (MOLAP), and an online hybrid analytical process (HOLAP) storage options for data. SQL Server analysis services also offer support for XML for the analysis standard as the principal communication protocol.

PostgreSQL vs SQL Server: Head-to-Head Comparison

With an idea of the key aspects of SQL Server and PostgreSQL, let's dig into the differences between the two. Use the elements that are listed below to figure out the one that will meet your needs best.

Accessibility

PostgreSQL provides a variety of solutions that ensures an extremely high level of service for its users. These include write-ahead log shipping, shared-disk failover, partitioning data, and various replication methods. Tools such as EDB Postgres Failover Management provide automatic failover , which ensures the highest availability of your database by monitoring failing databases and reporting them.

However, SQL Server includes various tools for high availability, such as log shipping, failover clusters, and replication. SQL Server's availability groups that work round the clock provide automated failovers when certain conditions meet. However, this offering is only available within the enterprise edition of SQL Server.

Data Structure and Table Structure

PostgreSQL offers the procedural PL/pgSQL programming language for its customers for ease of use. Additional functionalities to regular SQL in PostgreSQL include user-defined types, custom modules, extensions, JSON support, and extra options for triggers and various other functions.

SQL Server uses T-SQL, which bears resemblance to standard SQL. T-SQL includes additional support for strings and data processes, procedural programming, as well as local variables.

If you're trying to know how systems store and process requests, PostgreSQL isolates processes by treating them as separate OS processes. Each database has a separate memory that runs its own process. This makes monitoring and management extremely easy. However, at the same time, it makes scaling multiple databases harder.

SQL Server uses a buffer pool which can be capped or expanded based on the requirements for processing. All the work is done in a single pool, without multiple pages as opposed to PostgreSQL.

Both PostgreSQL and SQL Server provide support for temporary tables since it allows users to save intermediate results that are derived from branching complex processes and logic. Temporary tables are a great way to improve storage and efficiency of your database by isolating intermediary information and the primary information.

Defragmentation

If developers alter different components of the SQL database, these modifications take place at different points of the system and are difficult to monitor, read, and manage. Therefore, maintenance should also involve defragmentation -- which is the procedure of collating an modified database, assigning indexes, creating new pages, and revisiting the database structure. The databases can then free up the storage space on the disk that isn't being utilized properly so that a database is able to run at a quicker rate.

PostgreSQL analyzes the tables in a data layer to look for empty rows. It then get rid of any unnecessary components. By doing so it frees up storage space. However, this method needs lots of CPU power and could affect the program's performance.

However, SQL Server provides an effective garbage collector which doesn't create more than 15 to 20 percent of the expenses. In terms of technicality, developers are able to use garbage collectors on a continuous basis since it's that effective. To summarize, SQL Server offers more defragmentation methods than PostgreSQL.

Indexes

The way a database tackles indexes is an indication of its usability because indexes are used to pinpoint the data, without having to search for specific rows. You can also use indexes for reference to different rows or columns. The identical index to your files and display them in various locations within the database and gather all the pieces in a single.

PostgreSQL supports index-based table organization however, the earlier versions didn't use automatic index updates. Also, you can look up many indexes in the same search. This means that you can discover many details.

SQL Server provides rich automated capabilities for managing indexes. Indexes can be organized into clusters and keep the appropriate rows without any manual effort. SQL Server also supports partial indexes and multiple-index searches.

Features

PostgreSQL has no built-in job scheduler, unlike others SQL databases. Repetitive tasks need external tools like PgAgent, cron, or pg_cron on Linux as well as SQLBackupAndFTP and Task Scheduler on Windows.

Work within SQL Server however are easily scheduled using SQL Server Management Studio.

PostgreSQL offers well-thought-out Multi-Version Concurrency Control (MVCC) to handle several operations simultaneously. MVCC provides snapshots of database information to avoid displaying inconsistencies that result from simultaneous transactions, or data locking that takes place in different database systems. PostgreSQL utilizes serializable snapshot isolation (SSI) to guarantee the isolation of transactions.

SQL Server has a less developed multi-version concurrency control system and depends on locking of the data in order to minimize errors caused by concurrent transactions. By default. SQL Server also offers an optimistic concurrency function, which assumes that such issues occur rarely. Therefore, instead of locking a row, it's confirmed against the stored version in order to see the extent to which changes took place.

Partitioning and Sharding

Performance gains are crucial for larger databases when you've reached the limit of the stored procedures you have, as well as your hardware upgraded, you would need to spread the workload across various servers. Here's when partitioning and sharding come to play.

While both sharding and partitioning is essentially breaking down a large dataset into smaller subsets and sharding means that the data has been distributed across several computers, whereas partitioning doesn't.

In Version 10.0, PostgreSQL supports declarative partitioning -- partitioning by either list, range, or hash.

MS SQL Server supports horizontal partitioning -- splitting a table with lots of rows into multiple tables that have fewer rows.

MS SQL Server also supports sharding through Federation. "Federated Partitioned Views" are views where tables are spread across different servers in order to distribute the processing load.

For retrieving the data from servers, you need certain commands. These commands are known as divided partitioned or distributed views. They employ standard SQL statements, as well as the keyword UNION for drawing data from all the connected servers.

Likewise, DML statements (INSERT, UPDATE, and DELETE) can be used when specific rules are observed within the tables. Also, note that partitioned views federated are only supported by Enterprise editions.

While federated partitioned views may be used on any edition since there's not a distinct syntax to them, they won't be recognized as views that are federated. The requirements to recognise the view as split across servers are only available for enterprise editions.

Utilizing this method of partitioning, there's usually the performance increase of between 20% and 30 percent in the majority of applications. Therefore, it's an extremely efficient tool for any business that manages a lot of information.

Replication

While partitioning is splitting the database into smaller subsets and distributing the partitioned tables into different nodes, replication copies the database over multiple databases for a faster review and less time to respond.

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PostgreSQL has primary-secondary replication. It can be either asynchronous or synchronous. Write-ahead Logs (WALs) permit sharing of changes with replica nodes, hence making it possible to use asynchronous replication.

Other kinds of replicating mainly include logical replication, streaming replication, and physical replication.

• Logical replication follows a publish and subscribe model. Modifications depend on the identity of data replication, such as its primary key not its physical address.
• streaming replica essentially streams the WALs immediately after the file is created which allows standby servers to be quickly upgraded, rather than waiting for the file to be filled.
• Finally, physical replication is typically implemented using directories and files and without consideration for the contents within the physical location. PostgreSQL isn't able to support multi-primary replica in its own way, however it could be done with the aid of third-party tools.

SQL Server replication copies data from a publisher server to the subscriber. It could be either synchronous or asynchronous, depending of your SQL Server edition. It offers three types of replications: transactional replication, snapshot replication, and merging replication.

• Transparent replication is typically implemented for server-to-server environments, where modifications are sent via the publisher to the user as they happen.
• Merge replication is typically used when conflicts could occur, for server-to-client environments, or where data can be tracked and changed on either the subscriber or publisher . Then, it is transferred to the other.
• Snapshot replication is used when information is regularly updated and isn't required to be changed in a gradual manner, or when data replicates exactly the way it appears at a specific date. Additionally, the Enterprise edition provides peer-to-peer replication to provide an alternative to replication on multiple nodes.

Language & Syntax

PostgreSQL is developed in the C language. MS SQL is written in C and C++. Regarding language binding, PostgreSQL is very easy to access and to connect due to its API external the libpq, which is very carefully designed and thoroughly documented.

However, SQL Server external language bindings may depend on several other variables. You may require installing additional drivers or create classes to save the query data; thus you'd have to be aware of what information looks like when it's when it's being built. You would probably have to refer to the manual, and it could be rather lengthy to track down.

In terms of procedural language capabilities both PostgreSQL and SQL Server provide robust support. PostgreSQL supports JSON data type. JSON data type and users are able to use Python, Java, PHP, Perl, and R with SQL because they are supported by the procedural language feature.

Although SQL Server does provide support for this, it is still to be refined, because there are a few minor glitches that occur, and it could take a while to be implemented, as it's slow. It is necessary for the user to convert the code to the .dll file first.

In PostgreSQL it is not necessary to make a .dll file first. PostgreSQL is also able to provide a vast range of regular expressions (regex) as a foundation for analysis.

MS SQL Server comparatively has lower regex levels and does not support some functions like substrings, pattern index. It might not be as effective as PostgreSQL.

Performance

If it's about efficiency, PostgreSQL trumps SQL Server in many ways. The topic of partitioning has been discussed, and while both PostgreSQL as well as SQL Server offer partitioning, PostgreSQL gives it at no cost, with more efficiency.

PostgreSQL also offers more concurrency. It is an essential feature in which many processes have the ability to be able to access and modify shared information at the same time. The MVCC feature of PostgreSQL ensures a lesser possibility of deadlocks, but only stopping if two queries attempt to alter the exact row at the at the same time, and then serialize any changes performed to that row.

The MVCC lock that is used for querying data won't clash with locks that are used for writing data. This reduces the likelihood of lock conflict and enhances performance when for multiuser systems.

However, SQL Server has an insufficient concurrency and certain processes may even be deadlocked. In contrast to the MVCC feature, every time a row is updated the fresh version of the row is created instead of replacing the previous row, and the two versions remain. As time passes, older versions are transferred to a database system known as tempdb. Its concurrency is however a long way to go.

PostgreSQL has indexing features in a number of extensions. This improves the efficiency of the database.

However, SQL servers are yet to improve on the way they index data, and do not yet include arrays -- one of the most used variables.

Pricing

PostgreSQL was made available in the PostgreSQL License that is a free open-source license. PostgreSQL Global Development Group PostgreSQL Global Development Group remains committed to making PostgreSQL accessible as a free and free-of-cost software. The PostgreSQL Global Development Group has no plans to modify or even release PostgreSQL under another license.

MS SQL Server was released under a commercial license as an element of Microsoft products. Since the beginning of 2016, the database was made available to users for free. developers, but it is only compatible with one processor and 1GB of maximum memory. Although it's completely free, it lacks several functions that may be required in a commercial. There is the possibility of having to pay the amount of $899 per server should you require more servers. Recently, the SQL Server Enterprise Edition costs $13,748.

Scalability

The capacity of a database system to continue functioning properly when the amount of it is expanded to satisfy requirements of the user without degrading on its performance is called scalability.

PostgreSQL has many advantages in terms of scalability and can employ several CPU cores in order to implement parallel queries swiftly.

SQL Server can also use CPU cores. However, the standard version is limited to 24 CPU cores. Enterprise versions allow for the use of unlimited CPU cores. SQL Server also possesses a hyper-scale function, which means you can determine the lower and upper limits allowing users to scale down and upwards as per the requirements.

Security

Authentication Methods

On the server-side, PostgreSQL offers advanced authentication techniques, including light directory access protocol (LDAP) and pluggable authentication module (PAM), which potentially lower the threat to the PostgreSQL databases servers. Other security enhancements for the server side of PostgreSQL include PostgreSQL listen addresses for servers as well as host-based authentication and certificate authentication.

The security model of MS SQL Server, there are two security enhancements for servers. capabilities: Windows authentication mode and mixed-mode that enables an authentication method that works with both Windows Server and MS SQL Server. The security framework of MS SQL Server is a close integration of both the Windows authentication mode of Windows Server and the database.

Data encryption

PostgreSQL offers data encryption and allows you to use secure sockets layer (SSL) certificates whenever your data traverses the web or other public networks. You can also install client certificate authentication tools to be used as an alternative. In addition, you can employ cryptogenic features to save encrypted data into PostgreSQL that support both symmetric-key as well as public-key encryption.

Within MS SQL Server, the available data encryption features comprise transparency data encryption (TDE) Always encrypted and column-level encryption. TDE utilizes the latest encryption standard (AES) algorithm to secure physical files. These contain both log files. This feature is always encrypted, which lets you encrypt specific columns at any time, at rest or in motion (i.e. that the data is protected in memory as well).

User-Level Privileges

Furthermore, you have the ability to control the different accounts of users as well as their rights (read and write) in both PostgreSQL as well as SQL Server.

PostgreSQL includes user-level privileges such as role-based privileges at table level, and role inheritance. The auditing option allows you to review users' and groups' data-access actions in your database providing extra security.

SQL Server achieves this via the use of user groups and roles. Permissions for resources are given directly to the user's account and permissions are inherited from the parent resource.

You can also detect concurrency issues, lengthy queries, and normal workload metrics through monitoring and auditing activities in SQL Server.

Storage

Storage is among the main factors that determine a database's efficiency. Due to the increase in servers' processing power and large-scale memory support, it becomes almost essential for the databases to allow greater storage capacities in the database system.

PostgreSQL is an object-relational data source, while Microsoft SQL Server is a relational database system. This implies that PostgreSQL provides more sophisticated data types and allows object inheritance, though it also makes working with PostgreSQL much more difficult. It has a single ACID-compliant storage engine that initiates an entirely new system procedure with its memory allocation for every client connection. Thus, in order to increase the number of client connections on systems, more memory needs to be allotted.

SQL Server 2016 and above is able to run up to one hundred computers, or virtual machines. There is the maximum number of instances running per computer. This too is contingent on the edition. Enterprise edition allows the highest bandwidth and therefore greater storage capacity will be granted. While the latest standard edition allows for use of up to 128GB memory, it is possible to use unlimited memory in the enterprise version.

Support and Community

PostgreSQL provides updated versions on a regular basis and is available for download. Recently, the PostgreSQL Global Development Group has published an update for all versions supported of the database software, fixing over 55 bugs discovered over the past three months. PostgreSQL boasts a vast community of developers, third-party businesses, and fans who help each other and strive to further develop the system through fixing the reported bugs.

SQL Server releases a new version about every couple of years. The cost of support is based upon the conditions and terms of the license. Microsoft SQL Server also has a support community, in which developers, database analysts as well as system administrators and anyone interested in the platform may ask questions, or find out more about SQL Server through podcasts and webcasts, such as SQL Server Radio with Guy Glantser and Eitan Blumin, where users get to know a lot regarding the SQL Server and its compatibility with other Microsoft tools.

Both PostgreSQL as well as SQL Server can be paired with plugins. The pricing and compatibility depend on the particular plugin. Plugins can be helpful to organize, tidy, backup your database or more.

Triggers and Events

PostgreSQL has various advanced triggers you can choose from depending on your use case. Triggers supported are AFTER, BEFORE, and INSTEAD OF, and they are able to be utilized for insert, update, or DELETE events to manipulate the data. Like we said, PostgreSQL can run these triggers automatically and doesn't have to build the triggers into a .dll file before execution. These functions are used to execute a complex query when the trigger gets invoked.

SQL Server offers various triggers that can be used to trigger various types of database events, namely DML triggers DDL triggers and logon triggers

• DML triggers or triggers for data manipulation are triggers that allow manipulation of data, by inserting, updating, or even deleting records.
• DDL triggers are used to trigger data definition language (DDL) instances, such as dropping, creating, or altering the database.
• Triggers for logons can be used to trigger occasions of logon, such as when a user session is created. These triggers fire after successful authentication, and prior to establishing the user session. They can be useful in monitoring and auditing login activities.

Views

Views are basically tables which don't keep information physically. Views are typically utilized for security purposes to limit the access of users to information. Both PostgreSQL and SQL Server provide updatable views.

In PostgreSQL update, they don't take place automatically unless these conditions are met:

• The section should appear inside the FROM clause within the query in that view. It could be drawn from a table or an views of an updatable.
• There should be no window functions, aggregate functions, or functions for set-returning on the list of options.
• The query shouldn't contain the commands HAVING, LIMIT, DISTINCT, WITH, INTERSECT, EXCEPT, OFFSET and LIMIT at the highest level.

The views that are created using straightforward queries are able to be modified whereas it's almost impossible to update the ones created using more complex queries. However the more complex views can be changed applying rules. While PostgreSQL might not offer the capability to run materialized views, it has an option called matviews which could assist to rebuild any view that is materialized.

Within SQL Server, views can be automatically updated with both user-defined and system-defined views are supported. Additionally, two tables are updated simultaneously if they have different keys and the update command doesn't contain the use of more than one table.

In addition, users can utilize triggers to update intricate views. SQL Server also provides facilities for running materialized views which are commonly referred to as index views. Contrary to other materialized view types in relational databases, index views are synced with the database's data base and, as such, are regularly updated.

The shortcomings of SQL Server and PostgreSQL

Although we've gone over every detail about PostgreSQL as well as SQL Server, both have their drawbacks.

Although PostgreSQL is available for free, it isn't owned by a single organization. This is why it's struggled to establish an audience among its peers despite its prominent presence. PostgreSQL also focuses on compatibility more than speed. So, any modifications created for speed improvement demand greater effort.

However, SQL Server has often been criticized for its poor user interface. It is a complex set of performance tuning features and there is no native support for source control. When you're using SQL Server in your company, the business edition could make an in the pocket of your. SQL Server 2019 enterprise edition alone costs $13,748 -- that's like thirteen rooms worth in Ikea furniture! Furthermore, the licensing process can be difficult to grasp and it is constantly changing.

MongoDB is a document-oriented open-source, cross-platform database software which can be easily used to leverage documents that resemble JSON.

MariaDB, on the other hand, is a commercially-supported fork of MySQL whose pluggable and purpose-built storage engines support workloads that generally required a vast variety of different databases.

PostgreSQL vs SQL Server: What Database Do You Need to Choose?

Both PostgreSQL as well as SQL Server are widely used relational databases. But which one takes the cake? In the previous comparisons, PostgreSQL trumps SQL Server in a variety of situations. It's not just open-source and cost-free, but it also has several features that are easy to access and are able to be easily implemented as opposed to Microsoft SQL Server.

Moreover, PostgreSQL has a more appropriate concurrency management system. It can brilliantly handle cases in which multiple applications can access and edit shared information at the same time.

If you run an enterprise of a smaller size, PostgreSQL could be a good choice since it's totally free and comes with a variety of options to control the database. It's simple to install and it can be used on almost all kinds of operating systems. However, for businesses with significant investments into the Microsoft SQL Server stack, SQL Server has its benefits over PostgreSQL.

Summary

All in all All in all, PostgreSQL and SQL Server are functional and multi-faceted databases. While PostgreSQL is compatible with almost any operating system and is well-suited for small companies that need the most functionality, SQL Server is the most suitable choice for large companies, particularly those that require the utilization of Microsoft products.

In this post we've discussed the main difference in PostgreSQL and SQL Server, and their functions. The "right" choice will eventually depend on the way you intend to manage your company.

Between PostgreSQL and SQL Server, which will you choose to complete your next project and why? We'd love to hear about your opinions! Please share them with us via the comment area below.

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