Expanded Library

Integrate Couchbase 6 into Your Data Environment

by Kishan Iyer

In an environment with a number of specialized data analysis and management tools, data integration plays a significant role. This course covers the integration of data in Couchbase buckets with a variety of other commonly used data platforms.

What you'll learn

When using Couchbase, it is most likely one of the many tools in your environment which you use to store and manage your data. Each of these tools will have their own use case for how they work with your data. In this context, moving data between the various tools becomes a crucial, and potentially tricky, task. In this course we look at how to integrate your Couchbase database with a variety of other tools you may have in your environment, from search applications to data analysis platforms. First, you'll begin with a generic means of accessing Couchbase data, specifically, Couchbase views. You'll look at the MapReduce programming model which views are based on, how these can be defined and then invoked. Next, you'll move on to making Couchbase data available in other tools in your environment which are compliant with either JDBC or ODBC. You'll include demos to access data in your Couchbase buckets from Microsoft Excel and also Talend Open Studio. This course also looks into hooking up a Couchbase database with various big data tools in your environment using the specialized connectors offered by Couchbase. These include connectors for Apache Kafka, Apache Spark and Elasticsearch. Once you finish this course, you will recognize the need for integrating Couchbase with other data tools within your organization. And you will know precisely how to link a Couchbase database with a number of such data platforms.

Table of contents

Course Overview
2mins

About the author

I have a Masters in Computer Science from Columbia University and have worked previously as a developer and DevOps engineer. I now work at Loonycorn which is a studio for high-quality video content. My interests lie in the broad categories of Big Data, ML and Cloud.

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