GEM is a GUI for creating and managing an Elasticsearch index's datastructure mappings. ES Mappings provide an immutable interface to control how data is stored internally within Elasticsearch and how queries can be applied to it.
Mappings allow deciding things like:
Should a field with value '2016-12-01' be treated as a date or as a text field?
Should 'San Francisco' be stored as an analyzed text field to then run full-text search queries against it, or should it be kept non-analyzed for an aggregations use-case?
Should 'loc': ['40.73', '-73.9'] be stored as Object or should it have a geopoint datatype.
GEMtakes this a step further by providing an on-the-fly mapping inference based on user provided input data.
GEM supports three key mapping related options today:
Create data mappings with an on-the-fly auto inferencing capability.
Managing all the current data mappingswith an option to see the raw JSON data.