Product builder | People Developer | Engineering Management
What is common between these things?
(1) Sync your calendar, notes, contacts from mobile data to other devices.
(2) Team members collaborating using software, such as Google Docs, Trello.
(3) Large-scale data storage and processing systems on a public cloud like Amazon AWS, Microsoft Azure, or Google Cloud.
The answer is all such systems need to deal with the fact that the data may be concurrently modified. The fundamental idea is this: You have data. This data is stored on multiple replicas. You need to deal with conflicts across multiple replicas of data.
Broadly speaking, there are two possible ways of dealing with such data modifications:
There are two different categories of CRDTs:
Operation-based CRDTs replicas propagate state by transmitting only the update operation. For example, a CmRDT of a single integer might broadcast the operations (+10) or (−20). Replicas receive the updates and apply them locally.
State-based CRDTs send their full local state to other replicas.
Collaborative note-taking applications like Nimbus Notes uses CRDT for collaborative editing. Apple implements CRDTs in the Notes app for syncing offline edits between multiple devices.
Navigation application like TomTom uses CRDTs to synchronize navigation data between the devices of a user.
Distributed databases like Riak, Redis uses CRDTs for implementing globally distributed database.
In a world where most of the applications that we use on the internet are distributed in nature, CRDTs solves a fundamental problem in data storage and makes collaboration seamless and conflict-free.
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