PostgreSQL vs. SQL Server: How to Choose

When it comes to relational database management systems, two titans command the attention of developers, architects, and data professionals: the open-source PostgreSQL and Microsoft's SQL Server. The choice between them is far from trivial, impacting scalability, cost, and the very architecture of applications.

Let's dissect the core architectural differences of PostgreSQL vs SQL Server, the subtleties of their feature sets, and the practical implications of their respective designs. Below, we'll look at everything from concurrency control to custom data types, as well as the business side of things.

Architectural philosophies of PostgreSQL and SQL Server

The differences between PostgreSQL and SQL Server originate from their architectural philosophies. PostgreSQL, a product of the PostgreSQL Global Development Group, is a testament to the power of open-source collaboration. Its architecture is process-per-user, meaning each connection to the database forks a new server process. Such a design contributes to its stability and isolation, as a crash in one backend process typically won't affect others.

In contrast, Microsoft SQL Server employs a single-process, multi-threaded architecture. A single sqlservr.exe process manages a pool of worker threads to handle incoming client requests. This approach is more memory-efficient in environments with a large number of connections, as threads share a common memory space. However, it also means that a critical issue in the single process can impact the entire database server.

Concurrency control: the MVCC and locking

You'll find one of the most significant distinctions in how these two relational database management systems handle concurrent access to data. PostgreSQL employs a Multi-Version Concurrency Control (MVCC) model. Every transaction sees a snapshot of the data as it existed at the beginning of that transaction. When a row is updated, PostgreSQL creates a new version of that row rather than overwriting the old one.

It's an elegant approach, which means that readers don't block writers, and writers don't block readers, leading to exceptional performance in mixed read/write workloads. The downside is the need for a periodic cleanup process, VACUUM, to remove old dead row versions and prevent table bloat.

SQL Server, conversely, relies on a more traditional locking mechanism. It has evolved to include optimistic concurrency models using row versioning in certain isolation levels (like READ_COMMITTED_SNAPSHOT), but its default behavior involves acquiring locks on resources (rows, pages, or tables) that are being accessed.

It's often the reason behind blocking and deadlocks in highly concurrent environments, which require careful query tuning and transaction management to mitigate. Although SQL Server's lock manager is highly sophisticated, the fundamental difference in approach makes PostgreSQL a more attractive option for apps with a high degree of concurrent data modification.

Data types and extensibility

PostgreSQL is celebrated for its rich and extensible data type system. Beyond the standard SQL data types, it offers many advanced options, including native JSON support and JSONB (a binary version of JSON), hstore for key-value pairs, and a wide array of geometric and network address types.

PostgreSQL also allows users to define their own custom data types, operators, and functions. The extensibility is a win for apps with complex data modeling requirements because developers can embed domain-specific logic into the database.

MS SQL Server has a comprehensive set of built-in data types, but it is more constrained in its extensibility. It supports JSON as a NVARCHAR(MAX) type with a collection of functions for manipulation, but it lacks the native binary storage and indexing capabilities of PostgreSQL's JSONB.

For custom complex data types, MS SQL Server has the Common Language Runtime (CLR) integration, which allows developers to write custom types and functions in .NET languages. Often, it is a more complex way to implement and manage than PostgreSQL's native extensibility.

A good example of comparing PostgreSQL's vs SQL Server flexibility is its support for arrays of any data type. You can store denormalized data structures in a single column, which is advantageous in some scenarios. 

SQL Server databases do not have a native array type, and developers resort to workarounds like storing data in XML or JSON formats or using table-valued parameters.

Indexing in PostgreSQL vs SQL Server

Both SQL Server and PostgreSQL databases give you a variety of indexing strategies to optimize complex query performance, but their implementations and options differ. The standard B-tree index is the workhorse in both systems. However, PostgreSQL supports a wider array of specialized index types, including:

• Generalized Inverted Index (GIN). Ideal for indexing composite values where elements in the value are to be queried, such as arrays, hstore, and JSONB.

• Generalized Search Tree (GiST). A versatile index for many data types and query patterns, including geometric data and full-text search.

• Hash Indexes. Useful for equality comparisons, although their use has become less common with the improvements in B-tree performance.

• BRIN (Block Range Indexes). Suit very large tables where columns have a natural correlation with their physical location in the table.

Microsoft SQL Server, on the other hand, shines with its columnstore indexes, the best thing about its data warehousing capabilities. These indexes store data in a columnar format and lead to dramatic performance gains for analytical queries that aggregate large amounts of data from a subset of columns.

Microsoft SQL Server also has advanced features like filtered indexes and included columns, which give fine-grained control over index structure and performance.

High availability and disaster recovery

Every business needs the continuous operation of mission-critical databases. That's why both PostgreSQL vs SQL Server offer robust high availability and disaster data recovery features through different mechanisms.

PostgreSQL's native solution for high availability is streaming replication, where changes from a primary server are streamed to one or more standby replicas. You can configure this for synchronous or asynchronous replication and get a trade-off between data protection and performance.

For automatic failover, Patroni or repmgr are typically used (external tools). PostgreSQL also offers logical replication, a more granular control over what data is replicated and can be used for replicating between different major versions of PostgreSQL or to other database systems.

SQL Server's flagship high availability feature is Always On Availability Groups. It gives you a high level of data protection and automatic failover by maintaining multiple synchronized replicas of a database. SQL Server also has Windows Server Failover Clustering (WSFC) for instance-level high availability.

For disaster recovery, SQL Server has log shipping and database mirroring.

Security: PostgreSQL vs SQL Server

PostgreSQL's security model is based on roles and flexible access controls. It supports many authentication methods, including password-based authentication, Kerberos, and certificate-based authentication over SSL. It also provides row-level security, so you get fine-grained control over which rows a user can access.

As for data encryption, here PostgreSQL relies on filesystem-level encryption or third-party extensions.

SQL Server has a long history of robust security features, including built-in Transparent Data Encryption (TDE) for encrypting data at rest and Always Encrypted for protecting sensitive data in use. It also has fine-grained permissions, role-based granular access control, and integration with Active Directory for centralized user management.

Plus, SQL Server Analysis Services is a powerful platform for business intelligence with its own set of security features.

The ecosystem and tooling: open vs. integrated

The ecosystems surrounding PostgreSQL and SQL Server are a direct reflection of their origins. PostgreSQL thrives on a vibrant and active open-source community, which contributes extensions, tools, and support resources.

Popular tools in the PostgreSQL ecosystem are pgAdmin, a comprehensive database management tool, and many command-line utilities. The open nature of PostgreSQL has also led to a rich ecosystem of third-party vendors with specialized tools and support.

SQL Server's ecosystem is, unsurprisingly, tightly integrated with the Microsoft technology stack. SQL Server Management Studio is a powerful and mature integrated environment for managing SQL Server instances.

SQL Server Integration Services, SQL Server Reporting Services, and SQL Server Analysis Services all make a complete suite of tools for data integration, reporting, and business intelligence.

If you're heavily invested in the Microsoft ecosystem, the smooth integration of these tools with SQL Server is a significant advantage.

Performance: PostgreSQL vs SQL Server

I cannot say that one database is definitively "faster" than the other because performance is highly dependent on the specific workload, hardware, and configuration. But I can make some general observations based on their architectural differences.

PostgreSQL's MVCC architecture gives it an edge in read-heavy and mixed read-write workloads with high concurrency, as readers and writers do not block each other. Its extensibility also allows for highly optimized data structures and functions that can boost performance for specific use cases.

SQL Server, with its mature query optimizer and features like columnstore indexes, delivers exceptional performance for analytical and data warehousing workloads. Its in-memory OLTP capabilities give significant speed improvements for transaction-heavy apps.

Recent benchmarks show both relational databases performing admirably under many conditions. A 2024 comparison showed SQL Server with a slight edge in standardized OLTP benchmarks, and PostgreSQL handled a higher number of concurrent connections.

So, the best way to determine which database will perform better for your apps is to conduct your own benchmarks with realistic workloads.

Read more: How to Choose the Right Database for Your Needs

Licensing, support, and total cost of ownership

Perhaps the most stark contrast between PostgreSQL and SQL Server is in their economic models, which go beyond price tags and shape into the total cost of ownership. This total cost encompasses licensing, support, hardware, and operational overhead.

PostgreSQL

PostgreSQL is open-source, distributed under the PostgreSQL License, a liberal OSI-approved license. There are absolutely no licensing fees for using the software, regardless of the number of installations, cores, or users.

It's a great way to go for startups and cost-conscious organizations because you can allocate budget to other critical areas like development and infrastructure.

However, "free" doesn't mean zero cost. The TCO for PostgreSQL is comprised of:

• Support costs. The community support through mailing lists and forums is robust, but enterprises require guaranteed service-level agreements with third-party vendors. They offer 24/7 support, expert consulting, and enterprise-grade tools. These support contracts range from a few thousand dollars to tens of thousands annually.

• In-house expertise. Running PostgreSQL effectively and at scale requires skilled database administrators. The cost of hiring and retaining this talent is a big factor. Although the PostgreSQL talent pool is growing, finding experienced DBAs is still a challenge in some regions.

• Managed services (DBaaS). A popular way to mitigate the need for in-house expertise is to use a Database-as-a-Service provider, like Amazon RDS for PostgreSQL, Azure Database for PostgreSQL, and Google Cloud SQL for PostgreSQL. They offer fully managed services, including patching, backups, and high availability. So, instead, your development teams can focus on applications. The cost is a pay-as-you-go model based on instance size, storage, and data transfer.

More: Ispirer Systems — Amazon-verified migration partner

Microsoft SQL Server

Microsoft SQL Server is a commercial product with a more traditional and more complex licensing structure. Their primary licensing models are:

• Per core. Every physical core on the server running SQL Server must be licensed. There's a minimum of four core licenses required per physical processor. The model is ideal for web-facing workloads and situations where you can't easily count the number of users.

• Server + client access license. You purchase a license for the server and then a CAL for each user or device accessing the server. It's more cost-effective for internal apps with a limited number of users.

SQL Server comes in several editions: Standard and Enterprise are the most common for production environments.

• SQL Server Standard Edition offers core database capabilities but has limitations on features like the maximum memory and compute it can use, and lacks some of the advanced high-availability and security features of the Enterprise edition.

• SQL Server Enterprise Edition is the premium offering with the full feature set, including advanced high availability with Always On Availability Groups, Transparent Data Encryption, and extensive business intelligence capabilities. The cost per core for the Enterprise edition is way higher than the Standard edition.

For cloud deployments, Azure SQL Database offers a managed service with a flexible pricing model, based on Database Transaction Units (DTUs) or the vCore model. The vCore model gives more granular control over compute and storage resources and is more cost-effective for predictable workloads.

Read more: The Real Cost of Database Migration

Cost comparison table: key differences

Feel free to save for later this comparison of the potential costs associated with PostgreSQL and SQL Server database management systems. But note that they can vary depending on your specific requirements, region, and chosen vendors.

The choice between PostgreSQL and SQL Server from a financial perspective is a trade-off. With PostgreSQL, you're trading a lower upfront cost for potentially higher operational costs if you don't have the in-house expertise. With SQL Server, you're paying a premium for a highly integrated, enterprise-grade solution with a single point of contact for support.

For many, the open-source nature of PostgreSQL is a compelling economic advantage, but for organizations embedded in the Microsoft ecosystem, the convenience and comprehensive feature set of SQL Server justifies the higher price tag.

Making the choice: MS SQL Server vs PostgreSQL

The decision between PostgreSQL and SQL Server is not a matter of one being universally better than the other. It is a strategic choice that should be based on a thorough evaluation of your needs and priorities.

Choose PostgreSQL when:

• Cost is a primary concern. Its open-source nature eliminates licensing fees.

• You value flexibility and extensibility. The ability to define custom data types and functions is a major advantage.

• Your application has a high degree of concurrent read/write operations. MVCC shines in these scenarios.

• You are building applications on a non-Windows platform. PostgreSQL is platform-agnostic.

• You want to avoid vendor lock-in. The open-source community provides a safety net.

Choose SQL Server when:

• You are invested in the Microsoft ecosystem. The seamless integration with other Microsoft products is a big benefit.

• Your primary workload is data warehousing and business intelligence. Columnstore indexes and the BI stack are compelling features.

• You require enterprise-grade support and a single point of contact. Microsoft's support infrastructure is extensive.

• Your development team has deep expertise in T-SQL and the Microsoft stack. Taking advantage of existing skills will accelerate development.

• Your organization has a budget for commercial software and prefers a vendor-supported solution.

Anyway, both PostgreSQL and SQL Server are mature, powerful, and feature-rich relational database management systems. The "right" choice depends on a careful consideration of your technical requirements, your budget, and your long-term strategic goals.

At Ispirer, we know the fundamental differences in their architecture, features, and philosophies. If you struggle to pick one, reach out, and we'll help you make an informed decision that will serve your applications and your organization well for years to come!

People Often Ask

When to use PostgreSQL over SQL Server?

You might want to choose PostgreSQL when:

• Cost is a major factor. PostgreSQL is open-source and free to use, unlike SQL Server, which often requires expensive licenses.

• You're not tied to the Windows ecosystem. PostgreSQL runs on many operating systems, such as Linux, macOS, and Windows.

• You need more flexibility and advanced features. PostgreSQL supports unique data types and has powerful capabilities like table inheritance and multi-version concurrency control (MVCC) right out of the box. This MVCC system allows multiple users to read and write to the database at the same time with fewer conflicts, which is great for handling multiple transactions.

• Many developers find that PostgreSQL is excellent at handling complex queries and has strong support from the PostgreSQL Global Development Group, a dedicated community that continuously improves it.

When not to use PostgreSQL?

PostgreSQL might not be the right fit if:

• Your organization is invested in Microsoft products. SQL Server works in server-to-server environments with other Microsoft tools and services.

• You need top-of-the-line enterprise-level support. Yes, PostgreSQL has great community support, but SQL Server offers dedicated paid support from Microsoft, which large businesses need most.

• You rely on Windows-specific high-availability features. For things like Windows Server Failover Clustering, SQL Server is the natural choice.

Why choose SQL Server over PostgreSQL?

People often choose SQL Server because:

• It's user-friendly and easy to get started with. Many find its management tools more intuitive than what's available for PostgreSQL.

• It offers business intelligence and reporting tools. If your work involves a lot of data analysis and reporting, the tools that come with SQL Server are a big plus.

• In certain environments, especially optimized for Windows, newer SQL Server versions optimize query performance very well.

• It has strong security features. SQL Server provides advanced security options like Secure Sockets Layer (SSL) to protect your data.

Why is SQL Server better than PostgreSQL?

"Better" really depends on what you need. When comparing PostgreSQL and SQL Server, it's not about one being universally superior to the other.

SQL Server is considered "better" for businesses that are integrated with Microsoft's ecosystem and need a commercially supported database with enterprise features. SQL Server supports many programming languages and has a powerful version of the SQL language called T-SQL.

On the other hand, many argue PostgreSQL is "better" due to its open-source nature, lower cost, and advanced features. It's often favored for its ability to handle complex queries and its data consistency.

What is the difference between SQL and PostgreSQL?

This is a common point of confusion! Here’s the breakdown:

• SQL (Structured Query Language) is the standard language used to communicate with and manage relational databases. It's the core set of commands that you use to retrieve data, insert new information, and manage your database.

PostgreSQL (often just called "Postgres") is a specific database system. It's one of many database systems, like SQL Server, that uses SQL as its primary language. So, you use the standard SQL query language to interact with a PostgreSQL database.