Database Reference
In-Depth Information
Summary
In this chapter, we talked about using the AWS ecosystem to develop and deploy your ap-
plication on cloud. We started with AWS EMR integration with DynamoDB. We also used
AWS S3 as the staging environment for the integration. By creating the Hive table using
EMR, we also learned to query data in DynamoDB. This integration helped us to give data
analytics solution for your application. So that we don't need to go anywhere else, simply
keep your application database as DynamoDB and integrate with EMR to get better in-
sights from your data.
In the next section, we discussed how to integrate DynamoDB with AWS Redshift, which
is a data warehousing solution from Amazon. So if you need to stage out your data for
Business Intelligence applications, you can simply store it on Redshift.
In the last section, we talked about how to make your data searchable using the
CloudSearch engine. We saw how to create the CloudSearch domain from DynamoDB
tables and also used command-line options to configure the index for a given table. After
that, we explored options on uploading data from DynamoDB to CloudSearch.
I am sure that after reading this chapter you can see your end-to-end application running on
AWS Cloud without any overhead of maintaining so many systems.
In the next chapter, we are going to study a couple of use cases that are already implemen-
ted, and we will try to understand what we could do if we need to build something similar
to these systems.
