Applications get data from Couchbase Server in different ways - they can use basic key-value operations, secondary indexes (views) or full-text search. As a developer, how do you decide whether you should use secondary indexes or full-text search for your new app feature? This blog explains the differences between secondary indexes and full-text search indexes so that you know what you should use to access data in Couchbase based on the scenario you have at hand.
Visually, this is how a data structure for a secondary index looks like -
Using a B-tree data structure for secondary indexes optimizes quick key based lookups (in this case ‘Item name’) and range queries. For example, imagine that you are building a product catalog app and want to list all the product names that starting with ‘A’ till ‘F’. Using a secondary index in Couchbase on ‘item name’, only parts of the B-tree data nodes would need to be accessed.
So why use full-text search?
Imagine that you want to list all the products in your store having the keyword ‘red’ - this includes items such ‘red sweaters’, ‘red pants’ or even items with the color attribute ‘red’. A full-text search index maps document terms to the the list of document id’s - which means you can quickly get back the list of document id’s that have a particular term in them.
Couchbase server integrates with Elasticsearch, a full-text search engine. Using the Couchbase adapter for Elasticsearch, documents are replicated in real-time to Elasticsearch. Elasticsearch parses each document and builds a full-text index so that you can search across all your documents from your app.
The figure above shows how a full-text search index maps document terms found in the documents to document IDs. This data-structure is elegant for ad-hoc search querying - so for example, if you’re looking for “sweaters”, you get the document id’s relevant to Red and Blue sweaters.
Now that you understand about secondary indexes and full-text search indexes, let’s take a look at when you should use full-text search and when you should consider using a secondary index in your app.
You should use full-text search when :
- you want to search through large amounts of textual data such as web page content, blog posts, digital articles and, content metadata. Full-text search indexes will allow you to search across the entire dataset, across any attribute in addition to some relevance form of ranking the results.
- your app needs term based search.
You should use secondary search when :