Dear Team,
I hope this message finds you well. I have been reflecting on the current landscape of PL/SQL and its role in contemporary technology stacks. I would greatly appreciate your insights on a few points that have been on my mind.
PLSQL for Business Logic-still true ?
While it's widely acknowledged that "as long as there is Oracle, there will be PL/SQL," I am eager to explore forward-looking scenarios where PL/SQL remains a prominent choice for business logic. In today's context, it seems that business logic is predominantly implemented using modern object-oriented languages such as Java or .NET, leveraging features like Streams and Lambda functions. Could you provide examples or use cases where PL/SQL excels and is considered integral, especially in comparison to these object-oriented approaches?
PLSQL for Data Engineering -still true?
The ETL landscape has witnessed a significant shift towards technologies like Spark for seamless integration with data warehouses and data lakes. In this evolving scenario, I am curious to understand how PL/SQL continues to play a vital role in ETL processes. Are there specific use cases or examples where PL/SQL is still the preferred choice in modern data engineering stacks?
I understand the historical significance of PL/SQL in minimizing network calls and maintaining code proximity to databases, as highlighted in research papers advocating for a thick database approach.
However, I am keen to bridge the gap between theoretical advantages and practical implementations. Are enterprise projects aligning with this approach, or is the trend shifting towards business logic predominantly residing in Java/.NET environments?
In essence, could you kindly furnish examples and use cases illustrating
where PL/SQL stands out as a core, integral component in modern data engineering or application development stacks?
I am particularly interested in understanding if PL/SQL is now primarily considered a supplementary or exception-use or rather being used just because some comany don't upgrade due to finance or driven by compliance requirements rather than intrinsic value in data movement scenarios.
I appreciate your time and insights into this matter, and I look forward to hearing from you soon.