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But, range queries are not supported by the GIN index; asking for all products with the SIZE variations having value in a certain number range will not utilize the index. In cases like this, it is necessary to move some fields out of JSON documents to separate columns/tables and index them traditionally, using old and proven B-trees. In these instances, Mongo is more forgiving and flexible. It allows for strategies of the kind:

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He emphasises that the data Meta collects is more valuable than the glasses themselves. The more details that can be extracted from the user’s everyday life, the more accurately advertising and services can be targeted at the person.