Architectural complexity
Synchronizing data and indexes separately on disparate search and database systems is labor intensive and reduces productivity.
Full-text search makes it easy to search the contents of a database. Users specify the search text criteria, such as keywords, and the system scans one or more indexes for matches. Full text indexes are simple archives of information that are pre-organized to accelerate retrieval and solve requests faster than if the database were to scan every field individually.
Synchronizing data and indexes separately on disparate search and database systems is labor intensive and reduces productivity.
Using multiple vendors creates duplicate costs for search and database system licensing, training, and support, which makes the total cost of your technology stack considerably higher.
A multi-system architecture requires multiple points of management, which reduces overall security.
Search is a basic requirement for modern applications. With full-text searching you can easily add powerful and flexible search capabilities to your Couchbase applications. No additional Couchbase download or installation is required. Simply enable the feature, create an index, and start searching text right away.
You can use full-text search queries directly within a SQL++ query, eliminating the need to write complex code to process and combine the results from separate SQL and search queries.
Text search tools are integrated into Couchbase with built-in partitioning, replication, and auto failover for high availability. You can scale out full-text search easily with the distributed and scale-out architecture of Couchbase platform.
Index JSON data with powerful text analyzers in multiple languages. Flexible index on multiple fields, nested objects, and arrays.
Single index to support queries on multiple fields based on exact or fuzzy matches, and any combination of ANDs and ORs.
Reduce code complexity with full-text search queries directly within a N1QL query.
The engine behind Couchbase Full-Text Search is from the Bleve project – a powerful open source search and indexing library written in Go.
Aggregate data collected from different sources in one platform to build a single view of your customer or business.
Publish new product and inventory content in real time and scale to millions of products and requests per second to present the right data at the right time.
Enable field employees with one platform to manage data from different sources, push that data to the edge, and ensure that data is available online and offline.
Manage, support, and drive real-time data insights at the edge with embedded and cloud databases, sync, and guaranteed data availability.