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I have an app with approximately 20-40 million new documents added each month. Let's say these documents have approximately 4-8 fields I want to allow the user to search from. Not all entries are valid for a search and they will eventually expire from the table/collection, but I would like to create a quick search, where a customer can input something like a number or text, and an autocomplete input will return 5-10 top results. Depending on the type of search word (number/string), I can limit the query to specific fields, as some are numeric, rest are text based.

An example document in JSON format:

{
    "name": "Tesla Model S",
    "code": "tesla-model-s",
    "serial_number": "31289A90321SD",
    "shelf_number": 9387573,
    "inventory_id": 9093293828
}

Users need to be able to search from millions of documents (we can limit this to some degree), by writing a keyword such as Tes or model-s or 9387 and the data storage should return closest results. If the entry is numeric (9387) I can target the query to shelf_number and inventory_id but if it's a string, I can query fields such as name, code and serial_number.

Current options:

  • Relational databases support searching using LIKE, but not sure if the performance is optimal.
  • MongoDB requires numeric entries to be text for this. Can't search numbers like this.

What would you recommend?

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