What is the difference between Hadoop – AWS ELASTIC MAPREDUCE and AWS Redshift

You are correct, both Amazon EMR and Amazon Redshift can be scaled horizontally to provide more computing power Cluster system. However, there are some very obvious differences between these two services.

Amazon EMR provides Apache Hadoop and applications running on Hadoop. It is a very flexible system, Can read and process unstructured data, usually used to process big data. However, learning Hadoop and related technologies can be very difficult. (“Having rights is also given a great responsibility!”)

Amazon Redshift is a PB-level data warehouse accessed through SQL. Data must be loaded into Redshift before querying, which usually requires some conversion (“ETL”).

So which one to choose?

>If you want to use SQL and you have structured data (e.g. CSV files), then Redshift is the easiest solution.
>If you want to deal with unstructured data (e.g., use Strange format instead of structured CSV files), Amazon EMR can provide a very powerful Hadoop system.
>Sometimes people use it at the same time-use Hadoop to transform the data, and then use Redshift to query the data.

If Amazon Redshift can meet your needs, so please use it instead of Hadoop. Redshift is easier to use because it presents itself as a standard SQL database, which you can complete in a few minutes. All cluster stuff is behind the scenes, You don’t have to know too much to use it.

If you need more flexible features and don’t mind getting low-level and technical, then Hadoop on Amazon EMR will provide you with more features.

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I see that both AWS Elastic MapReduce and AWS Redshift use a cluster structure, which can be used for data analysis. What are their different use cases?

Amazon Redshift supports client connections with many types of applications, including business intelligence (BI), reports, data and analysis tools.

< p>Amazon Elastic MapReduce (Amazon EMR) is a managed cluster platform that simplifies the operation of big data frameworks (such as Apache Hadoop and Apache Spark) on AWS to process and analyze large amounts of data. p>

You are correct, both Amazon EMR and Amazon Redshift are cluster systems that can scale horizontally to provide more computing power. However, there is a gap between these two services Some very obvious differences.

Amazon EMR provides Apache Hadoop and applications running on Hadoop. It is a very flexible system that can read and process unstructured data, usually with For processing big data. However, learning Hadoop and related technologies may be very difficult. (“Having rights is also given a great responsibility!”)

Amazon Redshift is a PB-level data accessed through SQL Warehouse. Data must be loaded into Redshift before querying, which usually requires some conversion (“ETL”).

So which one to choose?

>If you want to use SQL and you have structured data (e.g. CSV files), then Redshift is the easiest solution.
>If you want to deal with unstructured data (e.g., use Strange format instead of structured CSV files), Amazon EMR can provide a very powerful Hadoop system.
>Sometimes people use it at the same time-use Hadoop to transform the data, and then use Redshift to query the data.

If Amazon Redshift can meet your needs, so please use it instead of Hadoop. Redshift is easier to use because it presents itself as a standard SQL database, which you can complete in a few minutes. All cluster stuff is behind the scenes, You don’t have to know too much to use it.

If you need more flexible features and don’t mind getting low-level and technical, then Hadoop on Amazon EMR will provide you with more features.

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