Elasticsearch
provides a robust, relaxing HTTP interface for assortment and
querying knowledge, designed on high of the Apache Lucene library.
Right out of the box, it provides climbable, efficient, and sturdy
search, with UTF-8 support. It’s a robust tool for assortment and
querying large amounts of structured knowledge and, here at Toptal,
it powers our platform search and can before long be used for
autocompletion furthermore. We’re large fans.
Chewy
extends the Elasticsearch-Ruby shopper, creating it a lot of powerful
and providing tighter integration with Rails.
Since
our platform is constructed victimization ROR developers in India, our
integration of Elasticsearch takes advantage of the
elasticsearch-ruby project (a Ruby integration framework for
Elasticsearch that gives a shopper for connecting to associate
Elasticsearch cluster, a Ruby API for the Elasticsearch’s REST API,
and varied extensions and utilities). Building on this foundation,
we’ve developed and free our own improvement (and simplification)
of the Elasticsearch application search design, prepacked as a Ruby
gem that we’ve named Chewy (with associate example app accessible
here).
Chewy
extends the Elasticsearch-Ruby shopper, creating it a lot of powerful
and providing tighter integration with Rails. during this
Elasticsearch guide, I discuss (through usage examples) however we
have a tendency to accomplished this, together with the technical
obstacles that emerged throughout implementation.