What is it?

Within distributed data architecture, not one but multiple computers are running the data. Distributed systems allow for high performance computing and resilience in case of data failure.

The power of distributed systems

Distributed systems can be perfectly applied to big data because they allow for growth. Tasks can be distributed and redistributed according to the amount of data that needs to be processed. Distributed systems also bring resilience in multiple different ways:

  • Load distribution increases performance of the individual systems
  • Replication of data increases safety and resilience, in case one or more systems fail
  • Processing speed is increased because the tasks are distributed

Task distribution

Multiple computers are performing different parts of tasks. This means that tasks can be completed much faster.

Geographical distribution

Computers in different locations are performing the same tasks. In case of an emergency, there will always be another computer to take over the task.

Replication

Replication ensures that a task will always be performed, no matter the circumstances, and there will always be copies.

Blockchain

Blockchain is an example of a transparant distributed system. It claimed renown in 2009 as the technique behind its first large-scale application: Bitcoin. But blockchain can be applied to so much more!

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