The road to infinite scalability.

1. NoSQL introduction
The road to infinite scalability
Ahmed Soliman
Head of Research and Development
Cloud Niners Information Systems L.L.C

2. @AhmedSoliman

3. www.ahmedsoliman.com

4. SQL Databases == RDBMS*
*yes, this a common convention

5. How do you scale a SQL
database?

6. clustering
partitioning
sharding
caching
partitioning

7. What is a database true
scalability?

8. Horizontal scale*
*more servers creates more capacity

9. Transparency
*business logic should be separated from concerns of
scaling server resources

10. No Single Point Of Failure

11. Ok, let’s see how SQL do?

12. Vertical Scalability*
* more capacity means bigger box

13. Horizontal Scalability*
*aka, partitioning or sharding

14. Read-only slaves

15. So, how to solve this
problem?

16. Simple!
By redefining the question :)

17. Is relational databases
always the right solution?

18. Relational properties*
*do you mean ACID?

19. Atomicity
Consistency
Isolation
Durability

20. Do you “really’ need that?

21. You might feel that you do

22. Trust me, you don’t

23. welcome
to
the
web
scale

25. More than 400 million active
users

26. Over 160 million objects
(pages, groups, etc.)

27. More than 25 billion pieces
of contents*
*links, videos, blog posts, notes, photos, etc.

28. SQL databases cannot
handle the web scale

29. Why?

30. It costs 100,000$ to setup a
SQL cluster*
*think of the hardware requirements

31. Cost is not proportional to
load

32. Cost is not proportional to
load
Although it should!

33. So, why is that?

34. This will be explained in the
next presentation(s)

35. enter
the
world
of
NoSQL

36. Non Relational

37. Key-Value store

38. Key = “value”

39. Based on DHT*
*distributed hash table

40. document store

41. Schema free database

42. {name: “mongo”, type:”db”}

43. PERFORMANCE

44. SQL Database
It takes SQL Server 2008
160 seconds to insert
50,000 rows

45. NoSQL Database
It takes MongoDB Server
5 seconds to insert the
same number of records

46. Man! This is REALLY fast.

47. Built-in Map-Reduce

48. Geospatial Support

49. Conclusion

50. Google, Yahoo, Facebook,
LinkedIn, Twitter, Digg, etc.

51. Horizontal scalability

52. Horizontal scalability
Commodity hardware

53. Horizontal scalability
Commodity hardware
High performance

54. Horizontal scalability
Commodity hardware
High performance
Fault tolerance

55. Horizontal scalability
Commodity hardware
High performance
Fault tolerance
Eventual consistency

56. Horizontal scalability
Commodity hardware
High performance
Fault tolerance
Eventual consistency *optional

57. Horizontal scalability
Commodity hardware
High performance
Fault tolerance
Eventual consistency *optional
And lots more...

58. Q&A