Tag: fts
Announcing General Availability of the C++ SDK for Couchbase
We are thrilled to announce the General Availability (GA) of the C++ SDK for Couchbase! This release adds support for native C++ language to our existing comprehensive set of SDK libraries in 11 programming languages and marks a significant milestone...
How to Build Indexes for Full-Text Search in Couchbase 7.0
Indexes are the underlying infrastructure that make full-text search possible. The new Scopes and Collections feature in Couchbase Server 7.0 makes full-text search in your applications more powerful than ever before. Powering those searches requires full-text indexes. This article provides...
How to Add Full-Text Search Functionality to Your JavaScript App
It’s unavoidable: If you’re working with a document database, you’re eventually going to need to search for (and through) your JSON documents. In this tutorial, you’ll add the full-text search capabilities of Couchbase to the basic REST API built with...
How to Use Full-Text Search across Couchbase Scopes & Collections
The Full-Text Search Service now offers better search performance and resource utilization across your cluster with the introduction of Scopes and Collections in Couchbase 7.0. Let’s take a quick step back: The 7.0 release of Couchbase Server introduces the concept...
FIRST CLASS SQL for FULL-TEXT SEARCH
Over time, the database industry has realized full-text search and SQL are two sides of the same coin. Text search needs further query processing, query processing needs text search to efficiently filter for text patterns. The SQL databases have added...
FTS and N1QL: Better MongoDB in Operator Performance Querying Multiple Arrays
Introduction Couchbase Full Text Search (FTS) is a great fit for indexing multiple arrays and executing queries with multiple filter predicates in arrays. In this article, I’ll demonstrate the advantages of using FTS over GSI (Global Secondary Index) for array...
Full Text Search Indexing Best Practices by Use Case
Introduction Full text search (FTS) indexing can be challenging for those who are not familiar with search in general. In this post, we’ll take some common search use cases and work through the creation of appropriate indexes following best practices...
Introducing FTS with N1QL
Topics this article will cover What’s good with N1QL? What about FTS? But why FTS within N1QL? Basic N1QL+FTS queries Deploying N1QL+FTS Syntax(es) Abilities & limitations N1QL+FTS Internals Covered-index vs Non-covered-index queries More N1QL+FTS query examples What’s next? 1. Couchbase’s...
Search & Rescue: 7 Reasons N1QL Developers Use Search
People don’t want a four key index. They need a four-ms response. Ted Levitt Application development is demanding. Each application is trying to progress on behalf of the customer — searching for the right product or the right form, ordering,...
N1QL & SEARCH: Leverage Full-Text Search (FTS) Index in N1QL
With Couchbase v6.5, Full-Text Search is now integrated into the Couchbase N1QL query construct. Customers can now leverage FTS indexes directly with N1QL. This provides developers a single API to combine N1QL exact predicate matching and FTS powerful searching. The...
Building a Shazam-like app to understand how Tokenizers and Filters work | FTS Part 2
In the previous blog post, we talked about why full-text search is a better solution at scale to implement a well-designed search in your application. In this second part, we are going to deep-dive on the Inverted Index and explore...
Create a Full Text Search Typeahead With Go, jQuery, NoSQL
About a week ago I write a tutorial for implementing a typeahead search with Node.js and jQuery. A typeahead is one of many great use-cases when using full text search (FTS), but it certainly isn’t the only use-case. As many...
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