Tag: JSON
Data Structures & Queries with Couchbase N1QL (SQL for JSON)
In the Data Structures for NoSQL Applications post, we used simplified JSON data access through native collections, maps, and more. This post demonstrates querying that data using higher-level N1QL queries, the SQL-based language for JSON. Developers can focus on managing...
NoSQL Is Dead, Long Live NoSQL
Dynamo accelerated the NoSQL revolution that’s driving the database industry. Recently, Amazon announced PartiQL – A SQL-Compatible Query Language for their flagship NoSQL database Amazon DynamoDB. This has brought the NoSQL “re:evolution” full circle. It’s wonderful to see the collaborative research from UCSD and...
Halloween Problem: Solution in N1QL.
Learning SQL is easy; Implementing SQL, not so much. Halloween has come and gone. But, the tricks of the Halloween problem is here to stay! This has to be solved by databases every day. SQL made the relational database easy,...
Text Analysis within a Full-Text Search Engine
Full-Text Search refers to techniques for searching text content within a document or a collection of documents that hold textual content. A Full-Text search engine examines all the textual content within documents as it tries to match a single search...
Arrays in JSON: Modeling, Querying and Indexing Performance
Array is THE difference between the relational model and the JSON model. — Gerald Sangudi Abstract JSON array gives you flexibility in the type of elements, number of elements, size of the elements, and the depth of the elements. This...
Comparing MongoDB MQL with N1QL features in Couchbase 6.5
This is a short note reviewing the MongoDB MQL language features highlighted in the release blog: MongoDB 4.4: User-Driven Engineering. Ready for You. MongoDB 4.4 release has added a number of features for the MQL language. Couchbase released 6.5 earlier...
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...
Analyze This: MongoDB & Couchbase Analytics.
The purpose of computing is insight, not numbers. — Richard Hamming The spiral of running the business, analyzing what to change & what to change to, and then changing the business is an eternal one. Do the right analysis, your...
FHIR Data Model with Couchbase N1QL
Couchbase is a JSON database that has now become an alternative to the traditional RDBMS. It has achieved this, not only by providing the industry-leading Key-Value store and the same query and ACID translation capabilities that organizations have come to...
Couchbase Intro for MongoDB Developers and NoSQL Experts
Six thousand years ago, the Sumerians invented writing for transaction processing — Gray & Reuter By any measure, MongoDB is a popular document-oriented JSON database. In the last dozen years, it has grown from its humble beginnings of a single...
Flexible Query & Indexing for Flexible JSON Model.
Use N1QL when you’re in a JSON pickle. — Confucius For the JSON data model, the advice is to think of collections as tables, JSON document as denormalized rows and field names as columns – roughly. All this holds in...
Simple dataviz with N1QL and Google Sheets.
Do whatever it takes to present the data to aid analysis and thinking. — Edward Tufte How do you create graphs like these if you don’t already have some ready-made cool dataviz tool? You can run queries to wrangle the...