Enhancing Query Performance: Leveraging In-Memory Optimized Dates in Oracle 23ai

In-Memory Column Store

Unlike traditional row-based storage, The In-Memory Column Store (IM column store) stores tables and partitions in memory using a columnar format optimized for rapid scans. This columnar format is optimized for analytical workloads, allowing for efficient scanning of specific columns without needing to read entire rows. 

In-Memory Optimized Dates

To enhance the performance of DATE-based queries DATE components (i.e. DAY, MONTH, YEAR) can be extracted and populated in the IM column store leveraging the In-Memory Expressions framework. This approach enables faster query processing on DATE columns, significantly improving the performance of date-based analytic queries.

Oracle 23ai: New DELETE and MERGE Enhancements with Practical Examples

Introduction

For a long time, working with DELETE and MERGE in Oracle meant dealing with awkward syntax and unnecessary complexity, especially when joins or feedback from DML operations were involved. Oracle 23ai finally removes many of those pain points.

In this blog, I will look at three practical enhancements: join-based deletes using DELETE … FROM, capturing affected rows with DELETE … RETURNING, and retrieving results directly from MERGE operations using RETURNING.

Oracle 23ai: New UPDATE Statement Features and Practical Examples

 

Introduction

Oracle Database 23ai brings meaningful improvements to the UPDATE statement, making everyday data changes simpler and more intuitive. Long-standing limitations—such as complex join updates and extra queries to retrieve updated values—are now addressed with cleaner, more expressive SQL. Features like UPDATE … FROM enable direct join-based updates, while UPDATE … RETURNING allows immediate access to modified data. Native BOOLEAN support and the DEFAULT ON NULL clause further reduce workarounds and conditional logic. Together, these enhancements help developers write clearer, safer, and more maintainable UPDATE statements that better reflect real-world data operations.