Fix for PR1386 (#1401)

* Oracle case study

* Oracle case study, minor fixes

* JSON format inside tables, InfoBox and Warning components, Markdown imdage component

* Title modification

* Banner change, JSON in table format

* Banner change, JSON in table format, InfoBox, Danger

* Banner change, JSON in table format

* Banner change

* Applying blog style

* Rollback to previous version

* Oracle case study with right blog style.

---------

Co-authored-by: Benjamin Granados <40007659+benjagm@users.noreply.github.com>

Author: loiclefevre

pages/blog/posts/oracle-case-study.md

@@ -5,7 +5,7 @@ tags:
   - database
   - relational
 type: Case Study
-cover: /img/posts/2025/oracle-case-study/blog_frontpage.webp
+cover: /img/posts/2025/oracle-case-study/banner.webp
 authors:
   - name: Loïc Lefèvre
     photo: /img/avatars/loiclefevre.webp
@@ -594,13 +594,13 @@ With all this in place, our React frontend can now create the following form:
 
 ![React frontend with input form generated from an annotated Oracle Database 23ai JSON schema.](/img/posts/2025/oracle-case-study/form.webp)
 
-> Interestingly, whenever you change the schema annotation in the database, it is immediately reflected inside your browser once you refreshed it. You can try with:
-> ```sql
-> ALTER TABLE products MODIFY name ANNOTATIONS (
->   REPLACE "title" 'Product name'
-> );
-> ```
->
+<Infobox> Interestingly, whenever you change the schema annotation in the database, it is immediately reflected inside your browser once you refreshed it. You can try with:
+```sql
+ALTER TABLE products MODIFY name ANNOTATIONS (
+  REPLACE "title" 'Product name'
+);
+```
+</Infobox> 
 
 
 #### JSON Relational Duality View
@@ -721,7 +721,7 @@ Running the 2 queries above respectively returns the data in JSON format:
 |Wooden spatula|4.99|42|
 |Other nice product|5|10|
 
-> The `_metadata` object will contain additional information such as an `etag` that can be used for [optimistic concurrency control](https://docs.oracle.com/en/database/oracle/oracle-database/23/jsnvu/using-optimistic-concurrency-control-duality-views.html).
+<Infobox>The `_metadata` object will contain additional information such as an `etag` that can be used for [optimistic concurrency control](https://docs.oracle.com/en/database/oracle/oracle-database/23/jsnvu/using-optimistic-concurrency-control-duality-views.html).</Infobox>
 
 #### POST method
 
@@ -755,7 +755,7 @@ With 23ai, a check constraint can now be marked as [`PRECHECK`](https://docs.ora
 
 Once a check constraint is marked as `PRECHECK`, you have the choice whether or not to disable the check constraint on the table as the retrieved JSON schema with `dbms_json_schema.describe()` will contain the check constraints as well.
 
-> We do **NOT** advise to disable check constraints as it would allow inserting bad data into the relational tables directly. The remark about `PRECHECK` constraints is here to provide as much information as possible.
+<Danger>We do **NOT** advise to disable check constraints as it would allow inserting bad data into the relational tables directly. The remark about `PRECHECK` constraints is here to provide as much information as possible.</Danger>
 
 ```sql
 -- Mark check constraints as PRECHECK
@@ -1016,7 +1016,7 @@ select p.content.publishedDate.timestamp() + interval '5' day
 from posts p;
 ```
 
-> We use the item method `timestamp()` in the last statement above because otherwise the SQL dot notation would return a SQL `JSON` (by default in 23ai) on which we cannot apply an interval operation. However, because the value is already stored as `TIMESTAMP` inside the binary JSON format, there will be *no conversion* from `JSON` to `timestamp` here.
+<Infobox>We use the item method `timestamp()` in the last statement above because otherwise the SQL dot notation would return a SQL `JSON` (by default in 23ai) on which we cannot apply an interval operation. However, because the value is already stored as `TIMESTAMP` inside the binary JSON format, there will be *no conversion* from `JSON` to `timestamp` here.</Infobox>
 
 Last but not least, by enabling type casting, native SQL data type checks are also performed ensuring 100% fidelity between stored binary values in the encoded JSON and SQL data types. As a result, we can store not just the standard JSON data types but also the SQL data types inside the encoded binary JSON such as `NUMBER`, `DATE`, `TIMESTAMP`, `TIMESTAMP WITH TIME ZONE`, `INTERVAL`, `RAW`, `VECTOR`, etc.
 
@@ -1101,7 +1101,7 @@ Results:
 | {<br/>&nbsp;&nbsp;"firstName": "Bob",<br/>&nbsp;&nbsp;"address": "Paris",<br/>&nbsp;&nbsp;"vat": false<br/>}                            |Paris|Bob|false|null|
 | {<br/>&nbsp;&nbsp;"firstName": "Bob",<br/>&nbsp;&nbsp;"address": "Paris",<br/>&nbsp;&nbsp;"vat": false,<br/>&nbsp;&nbsp;"tableEvolve": true<br/>} |Paris|Bob|false|true|
 
-> The trigger executes asynchronously, hence not delaying DML response times, however, because of it being asynchronous, it may take a second before you will see the new virtual column.
+<Infobox>The trigger executes asynchronously, hence not delaying DML response times, however, because of it being asynchronous, it may take a second before you will see the new virtual column.</Infobox>
 
 ## Conclusion