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 Amazon Athena uses Apache Hive to define tables and create databases. Databases are a logical grouping of tables. When you create a database and table in Athena, you are simply describing the schema and location of the table data in Amazon S3\. In case of Hive, databases and tables don’t store the data along with the schema definition unlike traditional relational database systems. The data is read from Amazon S3 only when you query the table. The other benefit of using Hive is that the metastore found in Hive can be used in many other big data applications such as Spark, Hadoop, and Presto. With Athena catalog, you can now have Hive-compatible metastore in the cloud without the need for provisioning a Hadoop cluster or RDS instance. For guidance on databases and tables creation refer [Apache Hive documentation](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL). The following steps provides guidance specifically for Amazon Athena.
 
-![createbucket.png](https://s3.amazonaws.com/us-east-1.data-analytics/labcontent/reinvent2017content-abd313/lab1/createbucket.png)
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-1. In the **Create Bucket** pop-up page, input a unique **Bucket name**. It is advised to choose a large bucket name, with many random characters and numbers (no spaces). 
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-    1. Select the region as **Oregon**. 
-    2. Click **Next** to navigate to next tab. 
-    3. In the **Set properties** tab, leave all options as default. 
-    4. In the **Set permissions** tag, leave all options as default.
-    5. In the **Review** tab, click on **Create Bucket**
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-![createbucketpopup.png](https://s3.amazonaws.com/us-east-1.data-analytics/labcontent/reinvent2017content-abd313/lab1/createbucketpopup.png)
 
 ### Create Database