PostgreSQL vs. SQL Server: Which Is Better For You?

With the increasing need for efficient data management in modern businesses, choosing the best database is crucial for your application. PostgreSQL and Microsoft SQL Server are popular options to consider if you are looking for a relational database that can help you manage and streamline workflows. While both are powerful, feature-rich relational databases, they have critical differences that can influence your decision.

If you are wondering how PostgreSQL differs from SQL Server, you are in the right place. This article explores PostgreSQL vs. SQL Server, including their strengths, pitfalls, and use cases.

What Is PostgreSQL?

PostgreSQL is a robust open-source object-relational database system known for its data integrity, reliability, performance, and advanced features. It supports SQL and PL/pgSQL language that allows you to store and manage complex data workloads securely.

What Is an SQL Server?

SQL Server is a powerful, proprietary relational database management system powered by Microsoft Corporation. It uses Transact-SQL to help you store, manage, and retrieve data at a large scale for business intelligence and analytics, transaction processing, or machine learning.

The latest edition, SQL Server 2022 (16. x), is Azure-enabled and can run on the cloud or on-premises. SQL Server is known for its high availability and fast performance when managing complex data workloads.

Market Share Between PostgreSQL and SQL Server

According to Statista, as of June 2024, Microsoft SQL Server is the third most popular database system worldwide, and PostgreSQL stands at the fourth position.

PostgreSQL's estimated market share is 17.51%, while SQL Server's is 28.20%. The continuous innovation and development of both database systems ensure they remain competitive and relevant to the evolving businesses needs.

PostgreSQL vs. SQL Server: Key Differences

Based on your business requirements, you can choose a proprietary, enterprise-focused system like SQL Server or a versatile, open-source option like PostgreSQL. Here are the critical differences between PostgreSQL and SQL Server to help you decide which one meets your needs:

Performance

• Concurrency Management: PostgreSQL supports Multiversion Concurrency Control (MVCC), which allows multiple transactions to read and write data without blocking as it maintains multiple versions of data. MVCC can help reduce lock contention, enhancing performance in multiuser environments.

SQL Server, on the other hand, supports database isolation levels for concurrency management. However, higher isolation levels like Serializable involve more locks, leading to deadlock situations and potential performance issues in high-concurrency environments.

• Table Partitioning: PostgreSQL and SQL Server both support table partitioning but use different methods. SQL Server uses horizontal partitioning and allows for automatic sliding windows to manage these partitions. It also enables you to partition the tables by ranges and lists. In contrast, PostgreSQL uses table inheritance for partitioning and lets you partition the table by range, list, and hash key.

In the PostgreSQL vs. SQL Server performance comparison, Postgres performs better in terms of concurrency. For table partitioning, choose SQL Server if you require automated partition management methods, especially for handling large datasets, or PostgreSQL if you need diverse partitioning strategies.

Syntax

PostgreSQL allows you to query the database using SQL and PL/pgSQL, while SQL Server uses Transact-SQL (T-SQL). Both PostgreSQL and SQL Server have similar queries for data definition, manipulation, subqueries, joins, and views.

Let’s understand PostgreSQL syntax vs. SQL Server syntax differences from the following table:

Apart from this, PostgreSQL and SQL Server differ in case sensitivity, which can impact how you structure database queries and naming conventions. By default, PostgreSQL keywords and unquoted identifiers are case-insensitive because they are always converted to lowercase.

For example:

DELETE FROM My_Table
WHERE ID = 15;

It can also be written as:

dELETe FRoM my_table
WhEre id = 15;

However, identifiers can be case-sensitive if they are quoted.

DELETE FROM “My_Table”
WHERE “ID” = 15;

The above query can also be written as:

dELeTE FroM “My_Table”
wHERe “ID” = 15;

In SQL Server, identifiers are also case-insensitive. However, identifiers can be case-sensitive by changing the COLLATION property at the database or column level. COLLATION is a set of rules used for comparing and sorting text data. Let’s see an example of changing the collation of an existing column to be case-sensitive:

ALTER TABLE My_Table
ALTER COLUMN My_Column VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CS_AS;

Here, SQL_Latin1_General_CP1_CS_AS is the default collation for the English (US) locale.

Data Types

PostgreSQL and SQL Server support heterogeneous data types, including primitives, structured, JSON, XML, geometry, and more. When comparing SQL Server vs. PostgreSQL data types, you must know SQL Server has a native geography type to help you process geographical data. At the same time, Postgres supports the PostGIS extension to help you store and manage geospatial information.

Pricing

You can freely use PostgreSQL for any purpose. On the other hand, SQL Server provides free versions, including a full-featured developer edition for non-production use and an Express edition with limited features. For advanced features, you must utilize SQL Server’s paid versions, such as Standard or Enterprise editions.

Indexes

When comparing PostgreSQL vs. SQL Server query performance, Postgres has more advanced indexing techniques. PostgreSQL supports multiple indexes to access, sort, and filter the data faster. These include a Generalized Search Tree (GiST), a Generalized Inverted Index (GIN), a space partitioned GiST, and more.

SQL Server provides clustered indexes to sort the rows in the table or view based on primary key values. It also supports non-clustered indexes, which are stored separately from the table data, where each key value entry has a pointer to the record.

Scalability

PostgreSQL and SQL Server are highly scalable, maintaining efficient database performance as data volume increases. PostgreSQL utilizes multiple CPU cores for concurrent query execution, while SQL Server’s scalability varies by its edition.

In addition, SQL Server’s hyperscale feature separates the query processing engine from storage, allowing you to scale resources dynamically based on your needs. Hence, SQL Server would be more suitable than Postgres for analytical workloads requiring dynamic scaling.

Clustering

PostgreSQL provides server clusters but lacks native support for multi-master or active-active configurations. Tools like repmgr allow you to maintain these clusters effectively.

SQL Server utilizes Windows Server Failover Clustering (WSFC), which consists of independent servers to handle varying workloads. This ensures fault tolerance and high availability for applications and services. WFSC helps with both active-passive and active-active configurations.

Integrations

PostgreSQL allows you to integrate with various tools and platforms, such as pgpool-II, Docker, MySQL, Apache Kafka, MongoDB, Elasticsearch, Amazon Redshift, and more. These tools enable you to enhance PostgreSQL through features like load balancing, containerization, real-time data streaming, robust search functionalities, and advanced analytics. With all these integrations, you can scale, manage, and analyze your Postgres data efficiently.

In contrast, SQL Server can help integrate with Azure Purview, a unified data governance service that lets you manage and govern your SQL Server data on-premises, SaaS, or multi-cloud. You can integrate SQL Server with other Microsoft services, such as Synapse Link, which enables you to run near-real-time analytics on your SQL Server databases. SQL Server also allows you to integrate with Azure SQL Managed Instance for disaster recovery, which minimizes disruption to access the databases. 

Supported Operating Systems

PostgreSQL runs on all popular operating systems, including Linux, Windows, macOS, Solaris, OpenBSD, and more.

SQL Server, on the flip side, operates on Windows or Linux with Kubernetes support.

ACID Compliance

PostgreSQL and SQL Server are ACID-complaint to ensure robust transaction processing. Both databases use similar techniques to ensure ACID properties. However, differences exist in the number of isolation levels.

Isolation is the property that guarantees transactions are executed independently of one another. Postgres offers four isolation levels—Read Uncommitted, Read Committed, Repeatable Read, and Serializable, while SQL Server offers an additional level, Snapshot. Each level balances data consistency and concurrency differently. 

Full-Text Search

Full-Text Search (FTS) allows you to search for documents in database tables that match your query. The ‘tsvector’ and ‘tsquery’ data types help you leverage the PostgreSQL FTS capability.

To utilize FTS in SQL Server, you must first create a full-text index on the columns containing text data you intend to query. The full-text index can help store the words and their locations within the textual data.

Community and Support

PostgreSQL has a large and active open-source community worldwide. You can participate in forums, mailing lists, local user groups, international sites, events, and IRC. Postgres offers extensive documentation and user manuals about data administration, syntax, and advanced features.

SQL Server also benefits from a large community supported by Microsoft. You can engage in forums, Microsoft Tech Community, user groups, and events like the PASS Summit. Microsoft provides comprehensive documentation, guides, and tutorials on SQL Server through its official website.

Migration

You can migrate the data from one PostgreSQL version to a newer one using pg_dump programs. In contrast, you can transfer the data between SQL Servers using Microsoft’s copy database wizard, database backup restore, or generate scripts wizard.

However, these methods require manual intervention. For an automated approach, you can leverage Airbyte, a data integration and replication platform. Airbyte facilitates smooth migration from PostgreSQL or SQL Server to other destinations.

‍Why Choose Airbyte?‍

• Support for Pre-built and Custom Connectors: Airbyte provides more than 350 built-in connectors, which help you migrate data from varied sources to your destination. If you cannot find a connector of your choice, you can create one in minutes based on your needs using Airbyte’s Connector Development Kit or no-code connector builder.
• ‍Modern GenAI Workflows: You can streamline your AI workflows by loading semi-structured or unstructured data into vector store destinations like Milvus, Weavite, and more. You can further simplify your data integration process with Airbyte’s integrated support for RAG-specific transformations, including LangChain-powered chunking and OpenAI-enabled embeddings, all within a single operation.
• ‍PyAirbyte: An open-source library that helps access all Airbyte connectors using Python programming. With PyAirbyte, you can effortlessly build a data pipeline based on your business needs for smooth data integration.
• ‍Robust Security: Airbyte supports HTTPS, TLS, and SSL encryption mechanisms, role-based access controls, and single sign-on authentication that allow you to secure the data throughout your integration process. It also adheres to data security regulations like CCPA and GDPR.

Security

PostgreSQL provides column-level and row-level security, allowing you to limit access to specific columns or rows within a table based on defined policies. It offers data encryption with Secure Sockets Layer (SSL) certificates and advanced authentication like pluggable authentication module (PAM) and lightweight directory access control (LDAP).

Contrarily, Microsoft SQL Server supports transparent data encryption (TDE) and column-level encryption. Its always-encrypted feature helps encrypt specific columns at rest or in transit. SQL Server’s Windows authentication and mixed mode allow you to reduce attacks on SQL Server databases.

Ease of Use

PostgreSQL relies upon third-party graphical user interfaces (GUIs) such as pgAdmin and command-line tools like psql for database management and query execution.

In contrast, SQL Server Management Studio (SSMS), command-line utilities, or Azure Data Studio are the widely used GUIs for managing SQL Server databases.

PostgreSQL vs. SQL Server: Pros & Cons

The following section highlights PostgreSQL vs. SQL Server pros and cons.

Advantages of PostgreSQL

• PostgreSQL offers high extensibility, allowing you to define custom data types, create user-defined functions, and integrate code from various programming languages without recompiling your database.
• PostgreSQL supports Multi-Version Concurrency Control (MVCC) to manage concurrent transactions and reduce deadlock situations.
• Advanced security measures include SSL encryption, authentication modes, and defining user privileges.
• Foreign data wrappers, a PostgreSQL capability that allows you to connect with other data sources using a standard SQL interface.

Disadvantages of PostgreSQL

• Installation of PostgreSQL is not beginner-friendly.
• PostgreSQL is more focused on compatibility with SQL standards and requires additional manual effort to optimize query performance.
• PostgreSQL lacks a built-in job scheduler to manage tasks regularly.

Advantages of SQL Server

• SQL Server supports PolyBase, a data virtualization feature that allows you to access and query data from multiple sources in their original format and location without moving it into SQL Server.
• SQL Server provides convenient backup and data recovery features to facilitate quick restoration in case of data loss or system failure.
• SQL’s Intelligent Query Processing can help enhance the performance of existing workloads with minimal effort.
• Defragmentation involves reorganizing fragmented data on a disk. This process helps maintain the efficiency of data retrieval and storage, ensuring that the database runs smoothly.

Disadvantages of SQL Server

• SQL Server has no MVCC support and a high likelihood of occurring deadlock scenarios.
• The cost of licensing, support, and advanced features is high.
• You may need to upgrade your hardware to accommodate newer SQL Server versions.

PostgreSQL vs. SQL Server: Use cases

Let’s look at the various use cases of PostgreSQL:

• General-Purpose OLTP Database: If your organization is a startup, you can use PostgreSQL for data storage to manage large volumes of business transactions efficiently.
• ‍Business Intelligence: PostgreSQL’s Ubiq, a business intelligence and reporting tool, helps you analyze your business information and turn it into actionable insights for making smart strategic decisions.
• ‍Federated Hub Database: PostgreSQL serves as a federated hub that allows you to connect with other databases like NoSQL through JSON support and foreign data wrappers.

Following are some of the use cases of SQL Server:

• SQL Server Analysis Services (SSAS): Integrating SQL Server with SSAS can help enhance data mining and OLAP. The OLAP engine offers several data storage modes, including multi-dimensional OLAP, relational OLAP, and hybrid HOLAP. These modes provide efficient data storage with greater scalability and high-speed query performance.
• ‍Machine Learning Services: ML services in SQL Server allow you to run Python and R scripts with relational databases. This enables you to clean data, perform feature engineering, and train and deploy ML models, all within a database. ML services eliminate the need for moving data across the network or worrying about local computer memory constraints for advanced analytics.
• ‍Replication Services: SQL Server’s replication services allow you to synchronize and replicate database objects partially or entirely using a subscriber/publisher model.

The Verdict

PostgreSQL is a free, open-source object-relational database management system with advanced concurrency management and broad OS compatibility. SQL Server, on the other hand, is a proprietary, enterprise-focused solution with high scalability, efficient clustering, and robust security features.

While PostgreSQL is a great option for startups, SQL is well-suited for large-scale projects. SQL Server is an excellent choice for seamless integration with Microsoft products for efficient analytics and reporting. Ultimately, your choice should depend on your specific business requirements.

FAQs

Why is Postgres so popular?

Postgres is a free and open-source RDBMS solution with high scalability and reliability. It is relatively easy to implement and highly configurable.

Can I use PostgreSQL in SQL Server?

Though both use standard SQL query language, you cannot directly use PostgreSQL within SQL Server as they are different database systems.

Is Postgres a NoSQL database?

No. Postgres is an object-relational database management system that follows SQL syntax. However, it can work with semi-structured data types like JSON.

When should I use PostgreSQL?

If you prefer open-source, free-to-use software, you can use PostgreSQL. It minimizes the licensing costs without compromising on features.

How do I move from SQL Server to PostgreSQL?

You can move SQL Server data to PostgreSQL using a data integration platform like Airbyte. It offers numerous built-in connectors, CDC capabilities, robust security measures, and more for an efficient migration process.