The document discusses using structured and semi-structured data together in modern applications. It describes how MariaDB Server handles both types of data through features like dynamic columns and JSON functions that allow storing and querying JSON documents. The presentation provides examples of defining, creating, reading, updating, and constraining both JSON documents and dynamic columns to bring the flexibility of semi-structured data to the reliability of relational databases.

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!