akka persistence and eventuate

Akka Persistence and EventuateA CQRS/ES tool comparison

Martin Krasser (@mrt1nz) Freelance software developer/architect

History

Eventsourced Akka Persistence

Eventuate

7.2012 9.2013 1.2015

Similarities

Basis technologies

Scala

Akka actors

Akka streams

(Pluggable) storage backends

Akka actor

Actor

State

Behavior

Mailboxtransient

non-durable

Akka Persistence and Eventuate

Persist actor state via event sourcing

Event sourcing

Capture all changes to application state as sequence of events

Store events in event log (append-only)

Replay events to recover application state

Event sourcing

Commands - actions, can fail

Events - immutable facts

Event-sourced actor

Actor

State

Behavior

Mailbox

Command handler

Event handler

Command processingEvent-sourced actor

State

Command handler

Event handler

Event log


State

Command handler

Event handler

Command

Event log


State

Command handler

Event handler

Command

Event log

Events


State

Command handler

Event handler

Command

Event log

Events

Events


State

Command handler

Event handler

Command

Reply

Event log

Events

Events

State recoveryEvent-sourced actor

State

Command handler

Event handler

Event log

State recoveryEvent-sourced actor

State

Command handler

Event handler

Event log

Events (replay)

Akka Persistence and Eventuate

Separate command processing from query processing

CQRS

Command QueryResponsibility Segregation

Different data models for command processing and query processing

CQRS

Write model for command processing

Read model for query processing

CQRS

Can be well combined with event sourcing (CQRS/ES)

CQRS/ES

Write model

Event log

Command Query

Events (r/w) Events (r)

Command side Query side

Read model

Abstractions

Command side Query side

AkkaPersistence

PersistentActor PersistentView Source[E,M]

Eventuate EventsourcedActorEventsourcedView

EventsourcedProcessorSource[E,M]

*) work in progress

PersistentActor EventsourcedActor


State


Command handler


Event handler


Snapshot handler

DifferencesCommand side

At a glance

https://twitter.com/mrt1nz/status/573382831889653760

https://twitter.com/mrt1nz/status/573382831889653760

Consistency

Akka Persistence and Eventuate support strong consistency

Eventuate additionally supports relaxation to causal consistency

Akka Persistence

Enforces strong consistency on command side

PersistentActors must be global singletons

No actor/state replication

Eventuate

EventsourcedActors can be replicated

State replication via reliable, asynchronous event replication

Replication across locations (availability zones)

Replication

Location ALocation B

Location C

Replication

Location A

Application state

Location B

Location C

Replication

Events

Events

Location A

Application state

Location B

Location C

Replication

Command


Location C

Replication

Command XLocation A

Location B

Location C

Replication

Command X

Events

Events


Location C

Replication

Command X

X

X

Events

Events


Location C

Eventuate

Replicas writeable at all locations = multi-master

Write-availability during network partitions

EventuateWrite conflicts

detection

tracking

automated resolution

interactive resolution

Partition


Location C

Partition

Command


Location C

Partition

Command XLocation A

Location B

Location C

Partition

Command XEvents


Location C

Partition

Command X XEvents


Location C

Partition

Command

Command

X XEvents


Location C

Partition

Command

Command

X X

Y

Events


Location C

Partition

Command

Command

X X

Y

EventsEvents

Events


Location C

Conflict

XY XY

XY


Location C

Resolution

XY XY

XY

Interactive resolution

XY => Z


Location C

Resolution

XY

XY


XY => ZZ


Location C

Resolution

XY

XY


XY => ZZ

Events

Events


Location C

Resolution


XY => ZZ Z

Z

Events

Events


Location C

Eventuate

Strong consistency within location*)

Causal consistency across locations

Causality is tracked with vector clocks

*) relaxation to causal consistency also possible within location

Causal consistency example

Distributed chat application

FIFO reliable broadcast vs.

Causal reliable broadcast

Inspired by ACM article “Don’t Settle for Eventual Consistency”

http://queue.acm.org/detail.cfm?id=2610533

Causal consistency example

http://queue.acm.org/detail.cfm?id=2610533

FIFO rel. broadcastDC1

DC2

DC3

FIFO rel. broadcast

- Alice: Lost my wedding ring

Alice

DC1DC2

DC3

FIFO rel. broadcast

- Alice: Lost my wedding ring- Alice: Lost my wedding ring


Alice

DC1DC2

DC3



Alice

- Alice: Whew, found it upstairs

DC1DC2

DC3

FIFO rel. broadcast



Alice

- Alice: Whew, found it upstairs- Alice: Whew, found it upstairs

DC1DC2

DC3

FIFO rel. broadcast



Bob

- Alice: Whew, found it upstairs- Alice: Whew, found it upstairs- Bob: I’m glad to hear that

DC1DC2

DC3

FIFO rel. broadcast



Bob


- Bob: I’m glad to hear that- Bob: I’m glad to hear that

DC1DC2

DC3

FIFO rel. broadcast





- Bob: I’m glad to hear that

DC1DC2

DC3

Bob

FIFO rel. broadcast






DC1DC2

DC3

FIFO rel. broadcast

Causality violation!





- Bob: I’m glad to hear that- Alice: Whew, found it upstairs

DC1DC2

DC3

FIFO rel. broadcast

Retry

Causality violation!

Causal rel. broadcast




DC1DC2

DC3




Bob


DC1DC2

DC3




Bob


Causalitycheck

DC1DC2

DC3




Bob



Causalitycheck

DC1DC2

DC3




Bob



Causalitycheck

Causalitycheck

DC1DC2

DC3




Bob




Buffer Causalitycheck

Causalitycheck

DC1DC2

DC3







Retry

DC1DC2

DC3








- Alice: Whew, found it upstairs

Retry

DC1DC2

DC3








- Bob: I’m glad to hear that- Alice: Whew, found it upstairs

Retry

DC1DC2

DC3






- Bob: I’m glad to hear that- Alice: Whew, found it upstairsCausal re-ordering

DC1DC2

DC3


Causal consistency

Causally related events are delivered in same order at all locations

Concurrent events can be delivered in any order at different locations

DifferencesEvent log

“Local” event log

Eventuate

- LevelDB - Cassandra


Location C

“Local” event log

“Replicated” event log

Eventuate



Location C


EventsEvents

Events

Local event log

Storage order consistent withcausal order

Given the potential causality relation ➞ of events

Local event logs are linear extensions of ➞

Replicated event log

Same causal event storage order at different locations

Different total event storage order at different locations

Akka Persistence- LevelDB - Cassandra - EventStore - MongoDB - Kafka - … Location A

Location B

Location C

DifferencesEvent collaboration

Akka Persistence

PA

PA

PAPA

Event log:

private for writing

shared for reading (query side)

Eventuate

EA

EAEA

Event log:

shared for writing

shared for reading

EA

Event routing

EA

EA

EA

Event routing

EA

EA

EAe1

Event routing

EA

EA

EAe1

e1

Event routing

EA

EA

EAe1

e1

All

Topic

Aggregate id

…

Event routing

EA

EA

EAe1

e1

EAEA

e1

EA

e1

Location A

Location B

Location C

Event collaboration

State replication

Service interaction

Event collaboration

S2

S1

S1

S3

Location A

Location B

Location C

Event collaboration

S2

S1e1

S1

S3

Location A

Location B

Location C

Event collaboration

S2

S1e1

S1

e1

S3

Location A

Location B

Location C

Event collaboration

S2

S1e1

e1

S1

e1

S3

e1

Location A

Location B

Location C

Event collaboration

S2

S1e1

e1

S1

e1

S3

e1

Location A

Location B

Location Ce2

Event collaboration

S2

S1e1

e1

S1

e1

S3

e1

Location A

Location B

Location Ce2

e2

Event collaboration

Reliable, distributed and partition-tolerant business processes

Event-driven (micro-)service architectures

Event collaboration

Reliable event delivery

Causal event delivery

De-duplicated event stream

DifferencesQuery side

Akka Persistence 2.3PA

PA

PV

PV

PV

PersistentViews on single PersistentActor (default)

Akka Persistence 2.4PA

PA

S

S

S

Stream Sources for multiple PersistentActors(requires storage plugin support)

Eventuate

EV

EV

EventsourcedViews on multiple EventsourcedActors(default, shared local log)

EA

EA

EA

Eventuate

EV

EV

EventsourcedViews on multiple EventsourcedActors(default, shared replicated log)

EA

EA

EA

EA

EAEA

Location A

Location B

Location C

Consistency in CQRS

Eventual consistency

Causal consistency

AkkaPersistence

usually per PA(plugin-specific)

Eventuate

Causal consistency

Single EA/EV: default

Across EA/EV: conditional requests

Example scenario

Update a write model (EA)

Query a read model (EV)

Query result should include effect that was caused by the update

Conditional request

EA

Location A

EV

Location B

Conditional request

EA

Location A

EV

Location B

cmd

Conditional request

EA

Location A

EV

Location B

evt

cmd

Conditional request

EA

Location A

EV

Location B

evtevt(vts)

cmd

vts = vector timestamp (a “condition”)

Conditional request

EA

Location A

EV

Location B

evtevt(vts)

cmd reply(vts)


Conditional request

EA

Location A

EV

Location B

evtevt(vts)

cmd CR(query, vts)reply(vts)


Conditional request

EA

Location A

EV

Location B

evtevt(vts)



delay

Conditional request

EA

Location A

EV

Location B

evtevt(vts)evt(vts)



delay

Conditional request

EA

Location A

EV

Location B

evtevt(vts)evt(vts)



deliver

Conditional request

EA

Location A

EV

Location B

evtevt(vts)evt(vts)



reply

deliver

Akka Distributed Data and Eventuate

CRDTs

CRDTs

Conflict-free Replicated Data Types

Automated resolution of write conflicts

CRDTs

Akka distributed data: CvRDTs (convergent or state-based)

Eventuate: CmRDTs(commutative or operation-based)

CRDTs

CvRDTs CmRDTs

Message payload Current state Operations

Communication middleware No guarantees

Reliablebroadcast

(idempotent)

Change history CvRDT intern Persistent log

Specification

“A comprehensive study of Convergent and Commutative Replicated Data Types”

http://hal.upmc.fr/docs/00/55/55/88/PDF/techreport.pdf

http://hal.upmc.fr/docs/00/55/55/88/PDF/techreport.pdf

Akka CvRDTs

10 implemented from specification(incl. counters, registers, sets, maps)

In-memory only (non-durable)

Custom data types can be defined

Eventuate CmRDTs

4 implemented from specification(Counter, MV/LWW-register, OR-Set)

Durable via event sourcing

Eventuate CRDT framework

Documentationhttp://rbmhtechnology.github.io/eventuate/

http://doc.akka.io/docs/akka/2.4.0/scala/persistence.html

http://doc.akka.io/docs/akka/2.4.0/scala/persistence-query.html

http://doc.akka.io/docs/akka/2.4.0/scala/distributed-data.html

http://rbmhtechnology.github.io/eventuate/

http://doc.akka.io/docs/akka/2.4.0/scala/persistence.html

http://doc.akka.io/docs/akka/2.4.0/scala/persistence-query.html

http://doc.akka.io/docs/akka/2.4.0/scala/distributed-data.html

Thank you!

akka persistence and eventuate

Software