How does Amazon Redshift compare with Elasticsearch?
While the answer based on DB-engines.com includes very good details about the differences between the two, I think it misses the most important aspect which is the main uses of these two databases.
Amazon Redshift is a data warehouse aimed at large scale analytics. It is excellent for answering BI questions like customer cohort analysis, funnel analysis, etc.
Elasticsearch’s forte is it’s search engine. It is wonderful for full text search over the documents stored in it.
I believe that within one company you would most likely find both of them useful, each for it’s own purpose.
We ourselves at Alooma are using our own system to load millions of events per day into Redshift, which enables us to extract insights into our product usage, ad performance, sales pipeline, etc.
Here you can read more about different analytics use-cases with Redshift .
In addition, we are using Elasticsearch to implement one of our product’s core feature: the Restream queue. The Restream queue is an index of all events which failed to pass through the pipeline, enabling our users to easily understand what went wrong, and how the pipeline’s configuration should be adjusted in order to process and load these events successfully.
Of course you can also enjoy the best of both worlds and replicate your Elasticsearch data into Amazon Redshift for use in your analytics. You can read more about that here.
Published at Quora. See Original Question here