Postgres

This post is maintained by Bytebase, an open-source database DevSecOps tool that can manage both Postgres and SQL Server. We update the post every year. Update History Comment 2025/03/26 Initial version. Why Comparing PostgreSQL and SQL Server When comparing PostgreSQL and SQL Server, we're examining two enterprise-class database systems with different business models but similar capabilities. SQL Server represents the commercial approach with licensing costs and Microsoft ecosystem integration, while PostgreSQL offers comparable enterprise features (high availability, security, advanced SQL capabilities) as an open-source solution without licensing fees. This similarity in target applications, combined with PostgreSQL's feature parity and growing enterprise support ecosystem, makes it the natural first choice when organizations consider migrating away from SQL Server—offering a path to reduce licensing costs while maintaining enterprise-grade database capabilities. This comparison reflects the current state of both systems as of 2025, including the latest versions: PostgreSQL 17.4 (with PostgreSQL 18 on the horizon) and SQL Server 2025 (currently in preview): Feature Comparison Technical Specifications Development Workflow Pricing and Licensing Future Outlook Conclusion Feature Comparison Core Database Features Feature PostgreSQL 17.4 SQL Server 2025 Data Types Extensive built-in types including arrays, JSON, XML, geometric, network address types Comprehensive set including JSON, XML, spatial, and hierarchical data Indexing B-tree, Hash, GiST, SP-GiST, GIN, BRIN, covering indexes B-tree, Columnstore, XML, Spatial, Hash, Memory-optimized, Filtered Transactions ACID-compliant with MVCC ACID-compliant with various isolation levels Stored Procedures PL/pgSQL, PL/Python, PL/Perl, PL/Tcl, SQL T-SQL Views Regular, Materialized Regular, Indexed, Materialized Triggers Row-level, statement-level DML, DDL, Logon, CLR Partitioning Table partitioning, partition-wise joins Table and index partitioning, partition switching Constraints Primary key, Foreign key, Unique, Check, Exclusion Primary key, Foreign key, Unique, Check, Default Advanced Features Feature PostgreSQL 17.4 SQL Server 2025 High Availability Streaming replication, Logical replication, Synchronous/asynchronous replication Always On Availability Groups, Failover Cluster Instances, Database mirroring Scalability Read scaling via replicas, Connection pooling, Table partitioning Read scaling via Always On, Resource Governor, Elastic pools in Azure Security Role-based access control, Row-level security, Column-level encryption, SSL support Microsoft Entra ID integration, Always Encrypted, Dynamic data masking, Row-level security Cloud Integration Compatible with all major cloud providers Deep Azure integration, Azure Arc-enabled deployment AI/ML Capabilities Vector data type, pgvector extension for vector similarity search Built-in vector database, AI-powered query optimization, Intelligent Query Processing Extensibility Foreign Data Wrappers, Custom extensions, Pluggable storage Common Language Runtime integration, R and Python integration, Extensibility framework PostgreSQL-Specific Features Extensibility: PostgreSQL's architecture allows for custom data types, operators, and functions through its extension system. Foreign Data Wrappers: Allows PostgreSQL to connect to other data sources and treat them as local tables. Multi-Version Concurrency Control (MVCC): Provides efficient concurrent access without read locks. Point-in-Time Recovery: Allows restoration to any point in time using write-ahead logs. Full-Text Search: Built-in capabilities for text search with language support. Geospatial Support: PostGIS extension provides robust geospatial capabilities. JSON/JSONB Support: Native JSON types with indexing and querying capabilities. Table Inheritance: Supports table inheritance for object-relational designs. SQL Server-Specific Features In-Memory OLTP: Memory-optimized tables and natively compiled stored procedures. Columnstore Indexes: Highly compressed storage format optimized for analytical queries. Intelligent Query Processing: Adaptive joins, memory grant feedback, and approximate count distinct. Temporal Tables: Built-in support for tracking historical data changes. PolyBase: Technology for querying external data sources. Stretch Database: Dynamically extends warm and cold data to Azure. Graph Database Capabilities: Node and edge table types for graph data modeling. Microsoft Fabric Integration: Seamless integration with Microsoft's analytics platform. Technical Specifications Architecture PostgreSQL Architecture: Process-based architecture where each client connection spawns a new server process Shared memory used for caching and inter-process communication Write-Ahead Loggin

Apr 2, 2025 - 06:20

This post is maintained by Bytebase, an open-source database DevSecOps tool that can manage both Postgres and SQL Server. We update the post every year.

Update History	Comment
2025/03/26	Initial version.

Why Comparing PostgreSQL and SQL Server

When comparing PostgreSQL and SQL Server, we're examining two enterprise-class database systems with different business models but similar capabilities. SQL Server represents the commercial approach with licensing costs and Microsoft ecosystem integration, while PostgreSQL offers comparable enterprise features (high availability, security, advanced SQL capabilities) as an open-source solution without licensing fees.

This similarity in target applications, combined with PostgreSQL's feature parity and growing enterprise support ecosystem, makes it the natural first choice when organizations consider migrating away from SQL Server—offering a path to reduce licensing costs while maintaining enterprise-grade database capabilities.

This comparison reflects the current state of both systems as of 2025, including the latest versions: PostgreSQL 17.4 (with PostgreSQL 18 on the horizon) and SQL Server 2025 (currently in preview):

Feature Comparison
Technical Specifications
Development Workflow
Pricing and Licensing
Future Outlook
Conclusion

Feature Comparison

Core Database Features

Feature	PostgreSQL 17.4	SQL Server 2025
Data Types	Extensive built-in types including arrays, JSON, XML, geometric, network address types	Comprehensive set including JSON, XML, spatial, and hierarchical data
Indexing	B-tree, Hash, GiST, SP-GiST, GIN, BRIN, covering indexes	B-tree, Columnstore, XML, Spatial, Hash, Memory-optimized, Filtered
Transactions	ACID-compliant with MVCC	ACID-compliant with various isolation levels
Stored Procedures	PL/pgSQL, PL/Python, PL/Perl, PL/Tcl, SQL	T-SQL
Views	Regular, Materialized	Regular, Indexed, Materialized
Triggers	Row-level, statement-level	DML, DDL, Logon, CLR
Partitioning	Table partitioning, partition-wise joins	Table and index partitioning, partition switching
Constraints	Primary key, Foreign key, Unique, Check, Exclusion	Primary key, Foreign key, Unique, Check, Default

Advanced Features

Feature	PostgreSQL 17.4	SQL Server 2025
High Availability	Streaming replication, Logical replication, Synchronous/asynchronous replication	Always On Availability Groups, Failover Cluster Instances, Database mirroring
Scalability	Read scaling via replicas, Connection pooling, Table partitioning	Read scaling via Always On, Resource Governor, Elastic pools in Azure
Security	Role-based access control, Row-level security, Column-level encryption, SSL support	Microsoft Entra ID integration, Always Encrypted, Dynamic data masking, Row-level security
Cloud Integration	Compatible with all major cloud providers	Deep Azure integration, Azure Arc-enabled deployment
AI/ML Capabilities	Vector data type, pgvector extension for vector similarity search	Built-in vector database, AI-powered query optimization, Intelligent Query Processing
Extensibility	Foreign Data Wrappers, Custom extensions, Pluggable storage	Common Language Runtime integration, R and Python integration, Extensibility framework

PostgreSQL-Specific Features

Extensibility: PostgreSQL's architecture allows for custom data types, operators, and functions through its extension system.
Foreign Data Wrappers: Allows PostgreSQL to connect to other data sources and treat them as local tables.
Multi-Version Concurrency Control (MVCC): Provides efficient concurrent access without read locks.
Point-in-Time Recovery: Allows restoration to any point in time using write-ahead logs.
Full-Text Search: Built-in capabilities for text search with language support.
Geospatial Support: PostGIS extension provides robust geospatial capabilities.
JSON/JSONB Support: Native JSON types with indexing and querying capabilities.
Table Inheritance: Supports table inheritance for object-relational designs.

SQL Server-Specific Features

In-Memory OLTP: Memory-optimized tables and natively compiled stored procedures.
Columnstore Indexes: Highly compressed storage format optimized for analytical queries.
Intelligent Query Processing: Adaptive joins, memory grant feedback, and approximate count distinct.
Temporal Tables: Built-in support for tracking historical data changes.
PolyBase: Technology for querying external data sources.
Stretch Database: Dynamically extends warm and cold data to Azure.
Graph Database Capabilities: Node and edge table types for graph data modeling.
Microsoft Fabric Integration: Seamless integration with Microsoft's analytics platform.

Technical Specifications

Architecture

PostgreSQL Architecture:

Process-based architecture where each client connection spawns a new server process
Shared memory used for caching and inter-process communication
Write-Ahead Logging (WAL) for durability and crash recovery
Multi-Version Concurrency Control (MVCC) for transaction isolation
Extensible design with hooks for custom functionality
Catalog-driven operations and metadata management

SQL Server Architecture:

Thread-based architecture with a thread pool for handling client connections
SQLOS layer providing thread scheduling, memory management, and I/O services
Buffer pool for caching data pages in memory
Transaction log for durability and recovery
Lock manager for concurrency control
Query processor with cost-based optimizer
Storage engine with support for multiple storage formats

Index Capabilities

Basic Index Types

PostgreSQL	SQL Server	Notes
B-tree (default)	Nonclustered Index (default)	Standard balanced tree index for equality and range queries
N/A	Clustered Index	Determines physical order of data in table; PostgreSQL has no direct equivalent
Hash	Hash Index (memory-optimized tables only)	Optimized for equality comparisons
GiST (Generalized Search Tree)	Spatial Index	For complex data types like geometric or full-text search
GIN (Generalized Inverted Index)	Full-Text Index	For composite values like arrays and jsonb
SP-GiST (Space-Partitioned GiST)	N/A	For non-balanced data structures
BRIN (Block Range Index)	Columnstore Index (partial similarity)	For large tables with natural ordering
N/A	Columnstore Index	Column-oriented storage for analytics
N/A	XML Index	For XML data

Index Features and Options

PostgreSQL Feature	SQL Server Feature	Notes
Partial Index	Filtered Index	Index only a subset of rows based on a condition
Expression Index	Computed Column Index	Index result of expressions
Covering Index (INCLUDE)	Index with INCLUDE	Include non-key columns in leaf level
Unique Index	Unique Index	Enforce uniqueness constraint
Multi-column Index	Composite Index	Index on multiple columns
Index-Only Scan	Index Covering	Query satisfied entirely from index
Parallel Index Scan	Parallel Index Operations	Utilize multiple cores for index operations
Concurrent Index Creation	Online Index Operations	Create/rebuild indexes with minimal blocking
NULLS NOT DISTINCT	N/A	Allow multiple NULL values in unique index
Index Access Method	Index Type	Specify the index implementation
FILLFACTOR	FILLFACTOR	Control index page fill percentage
N/A	Included Columns	Non-key columns in leaf level
N/A	Indexed Views	Materialized view with index
N/A	Temporal Table Indexes	Indexes on system-versioned tables
N/A	Resumable Index Operations	Pause and resume index creation

Special Index Types

PostgreSQL	SQL Server	Notes
PostGIS Spatial Indexes (GiST)	Spatial Indexes	For geographic and geometric data
Full Text Search (GIN)	Full-Text Indexes	For text search capabilities
pg_trgm (GIN/GiST)	Full-Text Indexes	For trigram-based fuzzy search
JSONB Indexes (GIN)	JSON Indexes (2025)	For JSON document indexing
Exclusion Constraints	N/A	Enforce that no two rows return true for a specified operator
N/A	Selective XML Indexes	For specific paths within XML data
N/A	Memory-Optimized Indexes	For In-Memory OLTP tables
N/A	Columnstore Indexes	For analytical workloads
N/A	Graph Edge Constraints	For graph database relationships
Vector Indexes (ivfflat, hnsw)	Vector Indexes (2025)	For AI/ML vector similarity search

Development Workflow

SQL Server offers a more integrated development experience through DACPAC and SQL Database Projects, providing standardized tools for enterprise environments with strong governance requirements.

PostgreSQL offers a flexible approach using community and third-party tools, allowing for customized workflows but requiring more manual integration.

Bytebase streamlines database development workflows for both SQL Server and PostgreSQL, with specialized advantages for PostgreSQL users. It introduces project-based collaboration and Git-like schema version control to PostgreSQL environments, enabling teams to manage database changes with automated migration scripts, change reviews, and granular access controls.

Feature	PostgreSQL	SQL Server	Key Difference
Project-Based Development	Bytebase	SSDT, SQL Database Projects	SQL Server offers integrated project-based development with Visual Studio
Schema Definition	SQL scripts	SQL Database Projects, SSMS Diagrams	SQL Server provides declarative model for database definition
Schema Comparison	pgAdmin diff, third-party tools	SSDT Schema Compare, SSMS Schema Compare	SQL Server has more robust comparison tools
Version Control	SQL scripts	Native SSDT integration, DACPAC	SQL Server has better native source control integration
Build Artifacts	No standard format	DACPAC, BACPAC	DACPAC provides standardized build artifact in SQL Server
Deployment Packages	SQL scripts	DACPAC, SQLCMD	SQL Server offers more standardized deployment
Testing	pgTAP, custom scripts	SQL Server Unit Testing, tSQLt	SQL Server has integrated testing framework
CI/CD Integration	Custom scripts with standard tools	Native DACPAC/SSDT pipeline tasks	SQL Server has better standardized CI/CD integration

Pricing and Licensing

PostgreSQL Licensing Model

PostgreSQL is released under the PostgreSQL License, a liberal open-source license similar to the BSD or MIT licenses.

SQL Server Licensing Models and Pricing

Based on the latest SQL Server 2022 pricing

1. Core-Based Licensing

Edition	Price (USD)	Licensing Unit
Enterprise	$15,123	2-core pack
Standard (per core)	$3,945	2-core pack
Standard (server)	$989	Server
Standard (CAL)	$230	CAL
Developer	Free	Per user
Express	Free	Not applicable

Key Considerations for Core-Based Licensing:

Minimum requirement of 4 cores per physical processor
All cores in the physical processor must be licensed
Enterprise Edition includes unlimited virtualization rights
Software Assurance required for License Mobility

2. Server + CAL Licensing

Server license: $989 per server instance
Client Access Licenses (CALs): $230 per user or device

3. Modern Cloud-Based Pricing

Azure Arc-Enabled Pay-As-You-Go:

Edition	Monthly Rate (USD)	Hourly Rate (USD)
Standard per core	$73	$0.100
Enterprise per core	$274	$0.375

Subscription-Based Pricing:

Edition	Annual Price (USD)	Licensing Unit
SQL Server Enterprise	$5,434	2-core pack
SQL Server Standard	$1,418	2-core pack

Future Outlook

PostgreSQL 18 (Expected September 2025):

Query optimizer improvements including Hash Right Semi Join implementation
40% reduction in memory usage for joins with large datasets
15% faster execution times for EXISTS subqueries
Enhanced logical replication capabilities
Improved parallel query execution
Better integration with cloud environments

SQL Server 2025 (Currently in Preview):

Deep AI integration with built-in vector database capabilities
Enhanced security features including Microsoft Entra managed identities
Performance improvements including optimized locking
Intelligent Query Processing enhancements
Stronger cloud integration with Microsoft Fabric and Azure Arc

Conclusion

PostgreSQL and SQL Server represent two different philosophies in database management systems: the open-source, community-driven approach versus the commercial, integrated ecosystem approach. Both systems have evolved significantly and offer robust, enterprise-grade features in 2025.

PostgreSQL Advantages:

Zero licensing costs with a permissive open-source license
Extensive data type support and extensibility
Growing popularity and community support
Freedom from vendor lock-in

SQL Server Advantages:

Deep integration with Microsoft's ecosystem
Advanced business intelligence and analytics capabilities
Comprehensive enterprise features out-of-the-box

As both systems continue to evolve, they are likely to address their respective weaknesses while building on their strengths. PostgreSQL is gaining more enterprise features and commercial support options, while SQL Server is becoming more open and flexible with Linux support and containerization.