This whitepaper serves as an in-depth guide for database administrators (DBAs), software engineers, data architects, and even semi-technical managers who are planning or evaluating a migration from Microsoft SQL Server (MS SQL) to PostgreSQL. The migration process is rarely a one-click operation. It involves multiple layers of complexity such as schema translation, data type mapping, business logic conversion and security model adaptation.
Understanding which tool best suits your specific environment is key to a successful migration. This article explores the types of tools available, key evaluation criteria, and recommendations based on real-world use cases.
What Needs to Be Addressed?
The process of migrating from MS SQL to PostgreSQL involves more than just exporting data. Eventually, seamless migration requires a thorough understanding of what needs to be moved and how each component translates between the two platforms. Below is a checklist of elements that are typically migrated:
| Component | Considerations |
| Tables & Schemas | Differences in naming conventions, use of reserved keywords, and default behaviors may require adjustments. |
| Data Types | Not all MS SQL data types have direct equivalents in PostgreSQL (e.g., DATETIMEOFFSET, SQL_VARIANT). Custom types mapping might be necessary. |
| Indexes & Constraints | Indexes, unique constraints, and foreign keys must be re-evaluated for compatibility and performance implications. |
| Stored Procedures | Must be rewritten from T-SQL to PL/pgSQL that is usually the most difficult stage of the migration. |
| Views | Often contain T-SQL syntax that is incompatible with PostgreSQL; require manual rewriting or translation. |
| Triggers | Behavioral differences in trigger execution and syntax may affect application logic. |
| Users, Roles & Permissions | MS SQL and PostgreSQL use different security models; privileges must be redefined appropriately. |
| SSIS Packages | SQL Server Integration Services packages do not have direct PostgreSQL equivalents and must be redesigned using alternative ETL tools. |
| SQL Server Jobs | Job scheduling must be re-implemented using PostgreSQL-compatible tools like pgAgent or system-level schedulers such as cron. |
| Linked Servers | PostgreSQL offers Foreign Data Wrappers (FDW) to interact with external sources, but they function differently from MS SQL’s linked servers. |
Types of Migration Tools
Basically, migration tools can be categorized based on the tasks they perform. Understanding these categories helps in selecting the most appropriate tools depending on project needs:
- Schema Conversion Tools
These tools focus on translating database structure and metadata (for example tables, views, data types, stored procedures) from MS SQL syntax to PostgreSQL-compatible syntax.
- ETL/Data Transfer Tools
These tools are designed to efficiently migrate MS SQL data to PostgreSQL. They may support batch loads, full exports/imports, or real-time replication using Change Data Capture (CDC).
- Hybrid Tools
These tools offer both schema conversion and data transfer functionalities, often with some level of automation to streamline end-to-end migrations.
- Managed Services
Cloud vendors offer fully-managed migration tools integrated into their platforms, often with added support for high availability, scalability, and monitoring.
Tool-by-Tool Analysis: Strengths and Limitations
Below is a comparative assessment of popular tools used in MS SQL to PostgreSQL migrations, highlighting their unique advantages and limitations:
pgLoader
pgLoader is an open-source hybrid migration tool used primarily to load data into PostgreSQL databases. It's especially well-known for its ability to convert and migrate databases from other systems like MySQL, SQLite, Microsoft SQL Server and CSV files, directly into PostgreSQL with minimal manual intervention.
Features:
- Supports multiple source formats such as MySQL, SQLite, MS SQL Server, CSV, DBF and more
- Converts source database schema to PostgreSQL-compatible schema
- Parallel processing - uses concurrent threads for faster data loading
- Can transform data on-the-fly (e.g., change encoding, apply defaults, modify column types)
- Full migration support including schema, data, and indexes
- Command-line-based and scriptable, enabling automation and CI/CD integration
Limitations:
- Missing graphical user interface (GUI) may be difficult for less experienced users
- Schema conversion capabilities are relatively basic
- Does not adequately support conversion of stored procedures or business logic
In summary, pgLoader is best suited for small to mid-sized databases with relatively simple schemas and minimal procedural logic.
2. AWS SCT + DMS
AWS Schema Conversion Tool (SCT) and Database Migration Service (DMS) are key components of Amazon’s suite for cloud-based database migration, often used together to move databases from on-premises or cloud environments (including PostgreSQL, Oracle, SQL Server, MySQL, etc.) into Amazon RDS, Amazon Aurora, Amazon Redshift, or other AWS-managed services.
SCT converts database schema and code objects (e.g., stored procedures, functions, triggers) from one database engine to another, often from commercial engines (like Oracle or SQL Server) to open-source engines like Amazon Aurora or PostgreSQL.
DMS handles data migration between source and target databases with minimal downtime. It is often used after schema conversion via SCT.
Features:
- SCT automatically converts MS SQL tables, indexes and views to PostgreSQL
- STC converts stored procedures and functions to PostgreSQL-compatible code when possible
- DMS supports either full data migration or incremental ongoing data replication, reducing downtime
- DMS provides data type transformation, validation, and error handling
- Cloud-native and tightly integrated with AWS ecosystem
Limitations:
- Requires significant AWS expertise to configure and optimize
- SCT may need manual adjustments for complex conversions
In summary, AWS SCT + DMS approach is best suited for enterprises migrating MS SQL workloads to Amazon RDS for PostgreSQL or Aurora PostgreSQL.
3. Commercial Tools
There are several commercial tools available for migrating from Microsoft SQL Server to PostgreSQL. Each of them offers a variety of features tailored for enterprise use. Explicitly, these tools typically provide more automation, technical support, and enterprise-grade performance than open-source solutions. Here's a breakdown of popular commercial tools, their key features, pros, and cons.
Features:
- Typically feature-rich with intuitive GUI
- Support for a wide range of conversion scenarios, including logic-heavy databases
- Fast bulk data migration with multi-threaded processing
- Batch/automated migration via scripting
- Offer professional support and customization services
Limitations:
- Require licensing and may have subscription or per-database costs.
In summary, commercial migration tools are best suited for large-scale or mission-critical migrations requiring minimal manual intervention and high automation.
Evaluation Criteria for Tool Selection
Selecting the right tool for migrating from Microsoft SQL Server to PostgreSQL depends on several technical and business criteria. Obviously, a well-chosen tool can significantly reduce migration time, costs, and risk of errors. Below are the key evaluation criteria to consider.
- Compatibility:
- Can the tool support the specific MS SQL version you're running?
- Does it support the flavor of PostgreSQL you’re targeting (e.g., self-hosted, AWS Aurora, Google Cloud SQL)?
- Schema Fidelity:
- Does the tool carefully map data types and convert T-SQL procedural entries to PostgreSQL equivalents?
- Does it support case sensitivity, sequences, or IDENTITY columns mapping?
- Are there mechanisms to log, review, and customize transformation rules?
- Data Integrity:
- Is data transferred reliably?
- Are full and incremental loads supported?
- Finally, does the tool validate post-migration data for consistency?
- Downtime Requirements:
- Does your business require near-zero downtime?
- If yes, prioritize tools that support real-time replication or CDC mechanisms.
- Budget Constraints:
- Open-source tools like pgLoader or Ora2Pg are cost-effective but may require more manual effort.
- On the other hand, commercial tools offer convenience and support but come with a price tag.
Intelligent Converters Software
Migrating from Microsoft SQL Server to PostgreSQL is often more complex than it initially appears, particularly when it involves more than just transferring raw data. In other words, organizations typically need to migrate not only the data itself but also the entire database schema and embedded business logic. This includes elements like stored procedures, functions, triggers, and even user-defined types or constraints, all of which may behave differently or require significant adjustment in PostgreSQL.
Given these points, relying on a single all-in-one tool is rarely effective. Most tools excel in one or two specific areas but fall short in others. Therefore, successful migrations usually depend on a carefully orchestrated toolchain, with each component focused on a particular aspect of the migration.
Intelligent Converters offers a suite of commercial-grade tools designed for users ranging from non-technical stakeholders to advanced database engineers:
- MSSQL-to-PostgreSQL - for initial database migration, the tool migrates all essential database objects (tables, views, constraints, etc.)
- MSSQL-to-PostgreSQL Code Converter converts T-SQL logic entries such as stored procedures, functions, and triggers into PL/pgSQL
- MSSQL-PostgreSQL Sync provides ongoing bi-directional synchronization between MS SQL and PostgreSQL using triggers to serialize incremental updates
Suitable combination of these tools is particularly useful for organizations looking for turnkey solutions with robust documentation and minimal manual overhead.
Suggested Tool Selection Based on Use Case
| Scenario | Recommended Tool(s) |
| Simple schema, low data volume | pgLoader, SSMA |
| Large enterprise-scale migration | AWS SCT + DMS, Azure DMS, Ora2Pg |
| Minimal downtime allowed | AWS DMS, pg_chameleon, Striim |
| Easy GUI and user experience prioritized | Intelligent Converters, SSMA |
Conclusion
As shown above, there is no universal "best" tool for migrating from MS SQL to PostgreSQL. The most effective solution depends on a variety of factors, including:
- The size and complexity of your existing MS SQL database.
- The level of procedural logic embedded in your T-SQL code.
- Whether your target PostgreSQL environment is on-premises or in the cloud.
- Your tolerance for downtime during migration.
- Your team’s technical skill set and familiarity with the tools.
Carefully evaluating your project’s specific needs and constraints will help you select the most appropriate tool or combination of tools, ensuring a smooth and successful migration journey.
