In building Raygun we have to deal with a constant stream of exception data (100’s of millions per month) which we structure into errors and occurrences which have a simple 1:N relationship.
A relational database engine is great at set based operations and has a very familiar and powerful querying syntax but we are increasingly facing data challenges where leveraging a relational model doesn’t make as much sense. In building Raygun we have to deal with a constant stream of exception data (100’s of millions per month) which we structure into errors and occurrences which have a simple 1:N relationship.
At first, using a relational model seemed to be a natural fit for this but over time we ran into three general problems:
Surely we must just need a more powerful database cluster? More RAM, more CPU? Sure, but what about when we add 10x our data volume?
Rather than just blindly scaling, I always like to look around and see what everyone else is doing incase there is a better way. It turns out these are the type of problems that are handled nicely by ElasticSearch.
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