With Oracle Database In-Memory, it is possible to populate individual columns of a table into the In-Memory Column Store. This is very useful for large tables, if only the frequently used columns should be populated to safe memory. The SQL syntax to define this seems to be straight-forward, but does not always work as expected.
Analytic Views, in combination with Attribute Dimensions and Hierarchies, are very useful for ad-hoc queries in a Star Schema. But how about the performance of this Oracle 12.2 feature? I wanted to know it and analyzed the execution plans of some simple queries.
Analytic Views are one of the main features for Business Intelligence introduced with Oracle 12c Release 2. They provide a lot of new possibilities for analytical queries on star schemas. This blog post gives an overview of the new functionality.
Oracle 12c Release 2 introduced Analytic Views, a new set of metadata objects that are very useful for Data Warehouses and Business Intelligence applications. In the first blog post about this new feature I will have a detailed look at two of the new object types: Attribute Dimensions and Hierarchies.
Virtual Columns in Oracle are a convenient feature to implement derived measures of a fact table. But in combination with Oracle Database In-Memory, it has an impact on performance – unless you use Oracle 12c Release 2.
There are many new extensions for Partitioning in Oracle 12c Release 2 (12.2). One of them is the CREATE TABLE FOR EXCHANGE statement. Some years ago, I wished to have this feature for a particular problem with hidden columns.
Hash keys can be used instead of sequence numbers to build surrogate keys in a Data Warehouse. This is often done in Data Vault environments, and there are some good reasons to do that. But there are also several issues and restrictions with hash keys. So, use hash keys only if you have good reasons for them. And if you decide to use hash keys in your Oracle Data Warehouse, make sure that you do it the right way.