Streamlining Oracle to Azure Hyperscale Citus Migration Compatibility Solutions

Oracle to Azure Hyperscale

In the rapidly evolving world of database technology, the shift from traditional relational database systems like Oracle to distributed systems such as Azure Hyperscale Citus represents not merely a change but a revolutionary leap forward. This migration embodies a paradigm shift towards scalability, performance, and cloud-native integration, signaling a transformative journey for organizations worldwide.

Understanding the Migration Context

Organizations choose to migrate from Oracle to Azure Hyperscale Citus for several reasons:

      • Scalability: Azure Hyperscale Citus enables horizontal scaling, making it easier to manage large volumes of data and concurrent users.
      • Cost Efficiency: Potential for lower operational costs compared to traditional on-premises or even cloud-based relational databases.
      • Performance: Improved query performance through distributed processing and the ability to scale resources dynamically.
      • Cloud-native Features: Integration with Azure services for analytics, AI, and machine learning projects.

Compatibility Challenges

Data Types and Structures

One of the primary hurdles in migration is the difference in data types and structures between Oracle and PostgreSQL, which Azure Hyperscale Citus extends. Oracle’s data types, such as NUMBER, VARCHAR2, and DATE, have nuances that may not have direct equivalents in PostgreSQL, necessitating careful mapping and sometimes data transformation. For instance:

      • NUMBER Data Type: Oracle’s NUMBER data type is highly flexible, supporting a wide range of numerical values with variable precision and scale. PostgreSQL offers NUMERIC and DECIMAL types for similar precision needs but deciding on the appropriate type and precision requires careful consideration.
      • VARCHAR2 and TEXT: While Oracle’s VARCHAR2 allows for specifying a maximum size, PostgreSQL’s TEXT type does not require a length specification, potentially leading to differences in data validation rules.
      • DATE and TIMESTAMP: Oracle’s DATE type includes both date and time, which can be confusing when mapped to PostgreSQL’s DATE (date only) and TIMESTAMP (date and time).
      • LOB Storage: Large objects (LOBs) like BLOB and CLOB in Oracle may need different handling in PostgreSQL to ensure performance and compatibility.

Stored Procedures and Triggers

Oracle and PostgreSQL use different procedural languages for stored procedures and triggers (PL/SQL for Oracle and PL/pgSQL for PostgreSQL). Migrating these objects requires translating the syntax and semantics, which can be non-trivial due to differences in language constructs and execution models. Challenges include:

      • Control Structures: Differences in control flow structures, such as loops and conditionals, can necessitate significant rewriting of logic.
      • Exception Handling: PL/SQL’s exception handling mechanisms can be more nuanced than those in PL/pgSQL, requiring careful consideration during migration.
      • Autonomous Transactions: Oracle supports autonomous transactions within stored procedures, a feature not directly available in PostgreSQL, necessitating the redesign of some transaction management patterns.

Performance Optimization Features

Oracle databases often utilize specific features for performance optimization, like index-organized tables, bitmap indexes, and materialized views, in ways that don’t directly translate to PostgreSQL’s capabilities. Migrating these features requires understanding their purpose and impact on performance in the Oracle environment and then finding equivalent or alternative strategies in Azure Hyperscale Citus:

      • Index-Organized Tables: Oracle’s index-organized tables, which store table data within the index for faster access, may require a combination of proper table design and indexing in PostgreSQL to achieve similar performance benefits.
      • Bitmap Indexes: Used in Oracle for low-cardinality columns to efficiently filter data, PostgreSQL does not directly support bitmap indexes. However, strategies like partial indexes or using the GIN index on array columns can offer alternative solutions.
      • Materialized Views: While both Oracle and PostgreSQL support materialized views, their implementation and refresh mechanisms differ. Understanding these differences is crucial for optimizing data access patterns and refresh strategies in the migrated environment.

Solutions and Best Practices

Embracing PostgreSQL Extensions

      • Utility and Compatibility Extensions: Beyond pg_stat_statements consider extensions like orafce, which provides Oracle compatibility functions, and pgcrypto for cryptographic functions. These can simplify the transition and enable similar functionalities in PostgreSQL.
      • Custom Extension Development: For highly specialized Oracle functionalities not covered by existing PostgreSQL extensions, consider developing custom extensions. PostgreSQL’s extensible framework allows for tailored solutions to specific needs.

Incremental Migration and Testing

      • Pilot Projects: Before committing to a full migration, conduct pilot projects or proofs of concept with critical segments of your database. This approach helps in understanding the impact on performance and identifying potential issues in a controlled environment.
      • Automated Migration Tools: Utilize automated migration tools and services to streamline the conversion of schemas, data, and stored procedures. However, always review and test the output of these tools, as they may not cover all edge cases or optimize for performance.

Training and Support

      • Online Resources and Communities: Take advantage of online training courses, forums, and PostgreSQL communities. The PostgreSQL community is active and supportive, offering a wealth of knowledge and resources for troubleshooting and learning.
      • Workshops and Webinars: Participate in workshops, webinars, and training sessions offered by Azure and PostgreSQL experts. These sessions can provide insights into best practices, advanced features, and tips for optimizing your migration and deployment.


While the migration from Oracle to Azure Hyperscale Citus presents its complexities, with thorough planning, leveraging the right tools, and employing strategic approaches, most compatibility issues can be effectively addressed. The adoption of PostgreSQL, along with the advanced scalability features of Azure Hyperscale Citus, unveils new opportunities for enhancing application performance and achieving unprecedented scalability. The path to migration may present challenges, but the benefits awaiting at the journey’s end make it a worthwhile endeavor.

For organizations looking to navigate this transition smoothly and efficiently, partnering with experts who have a track record of successful migrations is key. At Newt Global, we specialize in facilitating seamless transitions from traditional database systems to modern, scalable cloud solutions. Our team of experts is equipped with the tools, knowledge, and experience to ensure your migration to Azure Hyperscale Citus is executed with minimal disruption and maximum benefit.

If your organization is considering this migration, or if you have any questions about starting this journey, we encourage you to reach out. Contact us at to discuss how we can assist in unlocking the full potential of your database systems with Azure Hyperscale Citus.