All posts by Keshav Murthy

Keshav Murthy is a Senior Director at Couchbase R&D. Previously, he was Senior Director of Product Management at MapR, Senior Architect for IBM, with more than 20 years experience in database design & development. He lead the SQL and NoSQL query processing team IBM Informix database. He received a President's Club award at Couchbase, two Outstanding Technical Achievement Awards at IBM. Keshav has a bachelors degree in Computer Science and Engineering from the University of Mysore, India and holds eight US patents.

Couchbase for Oracle Developers – Part 1 : Overview

Back in November, we presented “Mindmap: Oracle to Couchbase For Developers”. You can see the slide deck here: http://bit.ly/2mPdJfo This blog series will cover the following topics, comparing Oracle and Couchbase from a developer perspective. This blog: Overview Architecture Database Objects...

/ January 17, 2018

Database Pagination: Using OFFSET and Keyset in N1QL.

Read the pagination background in my previous article: https://blog.couchbase.com/optimizing-database-pagination-using-couchbase-n1ql/ Pagination is the task of dividing the potential result into pages and retrieving the required pages, one by one on demand.  Using OFFSET and LIMIT is the easy way to write...

/ January 11, 2018

Comparing Couchbase Views with Couchbase N1QL & Indexing.

As Couchbase data platform evolved, services like N1QL and GSI Indexing handled the use cases Couchbase VIEWS used to handle and much more.  It’s logical to ask the comparative question between them.  Here is a table comparing both.  This is...

/ December 4, 2017

Create the Right Index, Get the Right Performance.

Introduction There are three things important in database systems: performance, performance, performance.  For NoSQL database systems, there are three important things: performance at scale, performance at scale, performance at scale. Understanding the index options, creating the right index, with the...

/ November 12, 2017

Optimizing Database Pagination using Couchbase N1QL.

Background: How does Google do it? When you google something or anything, it gives you back top relevant results, tells you an approximate number of documents for your topic — all under a second.   Here are some high-level pointers: https://www.google.com/search/howsearchworks/algorithms/...

/ November 2, 2017

N1QL: A Practical Guide. Second Edition

Two years and two weeks ago, on a crisp fall day at Wall Street in New York, we launched N1QL in Couchbase 4.0. Even before the launch, we had customers using pre-release N1QL because it solved the critical business problem:...

/ October 26, 2017

Learn N1QL in 10 Minutes: An Interactive Online Tutorial

N1QL is SQL for JSON. The goal of N1QL is to give developers and enterprises an expressive, powerful, and complete language for querying, transforming, and manipulating JSON data. The goal of N1QL is to give developers and enterprises an expressive,...

/ September 7, 2017
N1QL: A Practical Guide

N1QL: A Practical Guide

N1QL is designed to help developers easily develop applications to solve real-world problems.  Technically, N1QL is designed to give developers and enterprises an expressive, powerful, and complete language for querying, transforming, and manipulating JSON data. N1QL takes inspiration from SQL...

/ March 17, 2017

SQL for Documents (N1QL): Brief introduction to query planning.

SQL for Documents: Brief introduction to query planning.   I wrote earlier on the need for new kind of SQL and introducing SQL For Documents (N1QL).   In this blog, we’ll discuss query planning phase of N1QL in the upcoming Couchbase Sherlock release.  N1QL...

/ January 2, 2017

Concurrency Behavior: MongoDB vs. Couchbase

Multi-User Testing   David Glasser of Meteor wrote a blog on an MongoDB query missing matching documents issue he ran into.  It is straightforward to reproduce the issue on both MongoDB MMAPv1 and MongoDB WiredTiger engine. Here are his conclusions...

/ November 30, 2016