The document discusses the use of structured and semi-structured data in modern applications, particularly focusing on JSON in MariaDB Server. It outlines the differences between structured and semi-structured data, explains how MariaDB handles these types with features like dynamic columns and JSON functions, and provides multiple examples of working with JSON data. The presentation concludes with a Q&A session and thanks to the audience.

1. Using semi-structured data
in modern applications
Max Mether
VP Server

2. Agenda
• Structured and semi-structured data
• JSON in MariaDB Server
• Dynamic Columns in MariaDB Server
• Q&A

3. Structured and
semi-structured data
Together

4. What’s the point?
It’s not SQL vs NoSQL.
It’s not relational vs JSON.

5. What’s the point?
Your data can be structured and semi-structured.

6. JSON
RelationalAgility
Flexibility
Simplicity
Ubiquity
Safety
Reliability
Transactions
Data Integrity

7. What’s the difference?
Structured data is externally described
Semi-structured is self described

8. How does MariaDB Server handle it?
• Dynamic Columns
• JSON
• Virtual Columns to apply structured
• CHECK constraints with functions for validation

9. JSON functions
Read, write and query JSON with SQL

10. Structured and semi-structured data

11. Structured and semi-structured data
with JSON documents
Structured Semi-structured

12. Structured and semi-structured data
with JSON documents
Structure described by
the schema
Structure described
by the data

13. Example #1: definition

14. Example #2: create

15. Example #3: read (field)

16. Example #4: read (array)

17. Example #5: read (array element)

18. Example #6: read (object)

19. Example #7: query (field)

20. Example #8: row to JSON document
SELECT JSON_MERGE(JSON_OBJECT('name', name, 'format', format), attr) AS data
FROM products
WHERE type = 'M';

21. Example #9: update (field)

22. Example #10: update (create array)

23. Example #11: update (add array element)

24. Example #12: virtual column

25. Example #13: index

26. Example #14: constraints

27. Example #15: constraint violation

28. Dynamic Columns
Creating “per-row” columns

29. Dynamic Columns
“columns within columns”
Structured Semi-structured

30. Structured and semi-structured data
with dynamic columns
Structure described
by the schema
Structure described
by the data

31. Example #1: definition

32. Example #2: create

33. Example #3: read

34. Example #4: update

35. Example #5: constraints

36. Questions?

37. Thank You!