Applications running on production have much higher requirements. Not only do they need to be correct, they also need to be "always-on", handle a much bigger user load, and also be secure. Meet TypeDB Cluster, the TypeDB database for production-scale, built using the Raft replication algorithm. Join us for a walk through the underlying architecture and what value it brings to developers running an application at scale. Speaker: Ganeshwara Henanda Ganesh leads the development of TypeDB Cluster while also managing other aspects such as infrastructure and project management. His day-to-day work involves building concurrent and distributed algorithms such as Raft and the Actor Model. He graduated with an MSc of Grid Computing from University of Amsterdam, and has built several large scale distributed and real-time systems throughout his career.

1. Building a Distributed Database With
the Raft Replication Algorithm
Ganeshwara Hananda, Lead Engineer

2. Concepts
Reasoner
TypeQL

3. TypeDB
App

4. App
TypeDB

5. Cluster
App App App App
App App App App App
TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB
TypeDB Cluster: Tackling Complexity, At Scale

6. Cluster
App App App App
App App App App App
TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB
Scalable

7. Cluster
App App App App
App App App App App
TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB
Highly-available

8. Cluster
App App App App
App App App App App
TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB

9. Cluster
App App App App
App App App App App
TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB TypeDB

10. Cluster
App

11. Cluster
App

12. Cluster
App

13. A Closer Look

14. Cluster
DB 2
(Replica)
DB 1
(Replica)
DB 2
(Replica)
DB 1
(Replica)
DB 2
(Replica)
DB 1
(Replica)
App
Cluster, server and replica

15. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
App
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
Primary and secondary replicas

16. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App
Transaction read & write (primary-replica)

17. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Primary)
DB 1
(Secondary)
App
Transaction read & write (primary-replica)

18. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App
Transaction read (any-replica)

19. How does a client know which server to talk to?

20. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App
TypeDB-Client
Automated Failover /
Load-Balancing

21. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App
{ server=1: database=db1, role=primary, term=1 }
{ server=2: database=db1, role=secondary, term=1 }
{ server=3: database=db1, role=secondary, term=1 }
TypeDB-Client
Automated Failover /
Load-Balancing

22. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App
Grakn-Client
TypeDB-Client
Automated Failover /
Load-Balancing

23. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 2
(Primary)
DB 2
(Secondary)
DB 1
(Secondary)
DB 1
(Secondary)
App

24. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 1
(Secondary)
DB 1
(Secondary)
App

25. How do we replicate the data to all replicas?

26. Cluster
DB 2
(Secondary)
DB 1
(Primary)
DB 1
(Secondary)
DB 1
(Secondary)
App
Distributed systems: always start with the right assumptions

27. Cluster
DB 2
(Secondary)

28. Replicator: our Raft-based replication engine
Cluster
DB 2
(Secondary)
Replicator Replicator Replicator

29. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
Raft: Key Ideas

30. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Follower:0) (Follower:0)
(Follower:0)
(Secondary)
(Secondary) (Secondary)
Raft: Leader Election

31. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Follower:0) (Follower:0)
(Follower:0)
(Secondary)
(Secondary) (Secondary)
Raft: Leader Election
election:500ms election:300ms election:700ms

32. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Candidate:1) (Follower:0)
(Follower:0)
(Secondary) (Secondary)
(Secondary)
Raft: Leader Election

33. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Leader:1) (Follower:0)
(Follower:0)
(Primary)
(Secondary) (Secondary)
Raft: Leader Election

34. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Leader:1) (Follower:1)
(Follower:1)
(Primary)
(Secondary) (Secondary)
Raft: Leader Election

35. Cluster
DB 2
(Secondary)
Replicator Replicator Replicator
(Leader:1) (Follower:1)
(Follower:1)
(Primary)
(Secondary) (Secondary)
Raft: Leader Election

36. Cluster
DB 2
(Secondary)
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)

37. Cluster
DB 2
(Secondary)
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)

38. Cluster
DB 2
(Secondary)
App
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)
Raft: Replication

39. Cluster
App
Raft: Replication
Follower:1
(Secondary)
Log
Replica
Leader:1
(Primary)
Log
Replica
Follower:1
(Secondary)
Log
Replica

40. Cluster
App
Leader:1
(Primary)
insert $p isa person,
has name ‘Bob’
{ … }
Raft: Replication
Follower:1
(Secondary)
Log
Replica
Follower:1
(Secondary)
Log
Replica Replica
{ … } { … }

41. Cluster
DB 2
(Secondary)
App
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)
insert $p isa person,
has name ‘Bob’
{ … } { … } { … }
Raft: Replication
Replica Replica
Replica

42. Cluster
DB 2
(Secondary)
App
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)
insert $p isa person,
has name ‘Bob’
{ … } { … } { … }
{ … } { … } { … }
Raft: Replication

43. Cluster
DB 2
(Secondary)
App
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)
{ … } { … } { … }
{ … }
{ … }
{ … }
{ … } { … }
{ … }
{ … } { … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
Raft: Replication

44. Cluster
DB 2
(Secondary)
App
Leader:1 Follower:1
Follower:1
(Primary)
(Secondary) (Secondary)
{ … } { … } { … }
{ … }
{ … }
{ … }
{ … } { … }
{ … }
{ … } { … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
{ … }
Raft: Summary

45. Closing Remarks
- TypeDB Cluster: A scalable and highly available database for production
- Automatic failover / load-balancing
- Robust data replication based on Raft

46. More Innovations Coming Your Way