Tuesday, May 13, 2014

Roshi - a distributed storage system for time-series events

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Roshi implements a time-series event storage via a LWW-element-set CRDT with inline garbage collection. Roshi is a stateless, distributed layer on top of Redis and is implemented in Go. It is partition tolerant, highly available and eventually consistent.

At a high level, Roshi maintains sets of values, with each set ordered according to (external) timestamp, newest-first. Roshi provides the following API:

  • Insert(key, timestamp, value) 
  • Delete(key, timestamp, value) 
  • Select(key, offset, limit) []TimestampValue 

Roshi stores a sharded copy of your dataset in multiple independent Redis instances, called a cluster. Roshi provides fault tolerance by duplicating clusters; multiple identical clusters, normally at least 3, form a farm. Roshi leverages CRDT semantics to ensure consistency without explicit consensus.

Check out the Git here and more here

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