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Applying Blockchain to Event Sourcing

Event Sourcing pattern at the core requires an event store to maintain the events. What if we add these events as it arrives into a blockchain ? This should effectively make sure the events have not been tampered with. The plan would be to initiate typical blockchain mining after which the event is added to the “block-chain of events” — an “EventChain”.

The definite side effect is that until the mining is complete, the business transaction cannot be internally marked as complete. Considering the time typically taken for mining, this would probably be an offline job.

Tamper Proof

The typical challenges faced by organizations who employ event sourcing and the event store is about securing the events. What if the DB admin for the event store manages to inject/remove events ? The replayed events and resulting projections are no longer valid in this case. Event chains should solve this issue for typical event stores.

Exploit the distributed infrastructure.

For private event chains , where businesses do not want the chain nor events to be exposed, existing distributed systems/hosts can be exploited for mining. Your event store DB cluster hosts, event sourcing services hosts, API hosts, cache cluster hosts and others that are spread across geography could be exploited for the same.

GDPR Challenges

There are cases where regulations require personal data to be removed from all data stores. In our case, this is about removing the related set of events from the event chain. Without the event chain, removing events from the event store was quick and easy.

Resetting the event chain when events are required to be deleted is challenging especially if there have been many events after the event(s) in concern. This would require re-mining the rest of events after removing the event(s) that had personal data all the way down to the most recent event. As this is an extremely time and compute intensive operation, it’s not recommended to store events that contain personal data in the event chain.


As the events from the event store can be played back to recreate a state at a point in time (“projections”), we could in fact have “snapshots” to identify a specific projection in time. We could link this snapshot as a child branch to the main event chain tree such that it’s not required to recalculate the projections each time; while making sure the projections themselves have not been tampered with.

We could look at having many child branches/trees for the different filters/conditions too.

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