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PL/SQL versus Synapse and Snowflake
PL/SQL is a procedural language designed to be embedded in SQL statements. It is a powerful language that can be used to perform a wide range of tasks, including data manipulation, error handling, and complex logic. However, PL/SQL can also be difficult to maintain and update, especially for large and complex codebases.
Synapse and Snowflake are popular cloud-based data warehouses that offer a variety of features and benefits, including scalability, performance and cost-effectiveness. They also provide SQL-like languages that are more modern and easier for building artificial intelligence and machine learning applications.
Challenges of migrating PL/SQL to cloud
There are a number of options for converting PL/SQL code to cloud-native systems. Tools like SnowConvert from Snowflake and AWS Schema Conversion tool can apply for certain scenarios and there are manual conversion and other third-party tool options.
Even with these tools, migrating PL/SQL code to Synapse or Snowflake can be a challenging and time-consuming process. Challenges include:
- Understanding the legacy code – PL/SQL code can be complex and difficult to understand, especially for code that was written many years ago.
- Reproducing the functionality – The goal of the migration is to reproduce the same functionality as the legacy code in the new environment. This can be difficult to do, especially if the code is not well-documented.
- Testing the migrated code – Once the code has been migrated, it needs to be thoroughly tested to ensure that it is working correctly. This can be a time-consuming and error-prone process.
Using AI to overcome challenges and accelerate data modernization
When harnessed properly, artificial intelligence (AI) can help overcome a lot of the complexity that causes challenges when migrating to the cloud. Key areas where you can use AI to modernize your PL/SQL code in Synapse or Snowflake include:
- Analyze the legacy code – AI can help identify patterns, dependencies, other important information that can be used to make the code easier to understand and accelerate migration.
- Generate new code – using AI to replicate the functionality of the legacy PL/SQL code can save a significant amount of time and effort when converting to Synapse or Snowflake.
- Test the migrated code – testing the migrated code and identifying any errors or defects is a critically important and difficult step in the modernization process, which can be assisted with AI to ensure that the migrated code is working correctly.
Generative AI approach to PL/SQL code conversion
Generative AI opens new doors for confronting the issues of tedious code conversion and optimization to accelerate your data modernization journey. With our advanced knowledge of PL/SQL code and deep experience modernizing data in Synapse and Snowflake, Bitwise has created powerful modules for transforming and validating code, including:
- Code Converter – provides effortless conversion that automates code migration and modernization utilizing Gen AI. Its batch processing feature allows increased efficiency for automated PL/SQL conversion.
- Code Optimizer – assesses code with Gen AI and suggests optimization designed to your specific goals. Code optimizer reduces space complexity, time and improves error handling assuring fine-tuned performance.
- Code Documenter – automates the commenting and documentation process allowing a clear, comprehensible code base and can delve into variables, functions and defined objects. This not only enhances code readability but also adding to long-term maintainability.
- Migrated Code Validation Utility – provides support for heterogeneous data sources and file types using a unique approach of in-memory comparison without moving the data across data stores. The utility generates comprehensive comparison and summary reports with synopsis of mismatched data and overall comparison stats to pinpoint any potential errors.
Conclusion
AI-powered PL/SQL code conversion to Synapse and Snowflake can be a challenging task, but it is a necessary step for enterprises that are looking to modernize their data and move to the cloud. AI can be used to overcome the challenges of migration and accelerate data modernization initiatives.
While using AI can be a game-changer for modernizing your PL/SQL code in Synapse or Snowflake, building the right AI competencies and using optimal prompt engineering with Generative AI comes with its own set of challenges. Our team has gone through extensive trial and error to perfect the steps needed to effectively harness AI to successfully convert PL/SQL code. Explore our Data Migration and Modernization solutions to see how we accelerate PL/SQL code conversion.
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