--- title: "Getting Started with AWS Redshift" description: "Discover how to get started with AWS Redshift and a SQL cloud data warehouses with this ATA Learning tutorial!" canonical: "https://adamtheautomator.com/aws-redshift/" --- # Getting Started with AWS Redshift > Discover how to get started with AWS Redshift and a SQL cloud data warehouses with this ATA Learning tutorial! Source: https://adamtheautomator.com/aws-redshift/ --- ATA Learning Tap to hide [ ATA Learning ](/) * [Home](/) * [Tutorials](/tutorials/) * [Instructors](/author/) * [Advertising](/advertising/) * [Recommended Resources](/resources/) * [About Adam](/about-adam/) Search for: * [](https://twitter.com/adbertram) * [](https://github.com/Adam-the-Automator) * [](https://www.linkedin.com/company/adam-the-automator-llc) * [](/feed/) ![Getting Started with AWS Redshift](https://adamtheautomator.com/wp-content/uploads/2023/01/aws-redshift.jpg) # Getting Started with AWS Redshift [![](https://secure.gravatar.com/avatar/d05ab46ae71ee2393867f96cfec69e3a779ade5f81d9a519fc4d4fab1b177298?s=192&d=mm&r=g)Goodness Chris-Ugari](https://adamtheautomator.com/author/goodness-chris-ugari/)24 January 202311 min. read Categories: [Cloud](/category/cloud/) Tags:[AWS](/tag/aws/) Table of Contents * [Prerequisites](#prerequisites) * [What is AWS Redshift?](#what-is-aws-redshift) * [Creating an IAM Role to Manage the AWS RedShift Service](#creating-an-iam-role-to-manage-the-aws-redshift-service) * [Creating an AWS Redshift Cluster](#creating-an-aws-redshift-cluster) * [Connecting to an AWS Redshift Cluster](#connecting-to-an-aws-redshift-cluster) * [Loading Data into AWS Redshift Cluster](#loading-data-into-aws-redshift-cluster) * [Creating Tables via the Redshift Query Editor](#creating-tables-via-the-redshift-query-editor) * [Loading Data to Tables](#loading-data-to-tables) * [Querying a Cluster via the Redshift Query Editor](#querying-a-cluster-via-the-redshift-query-editor) * [Resizing an AWS Redshift Cluster](#resizing-an-aws-redshift-cluster) * [Deleting an AWS Redshift Cluster](#deleting-an-aws-redshift-cluster) * [Conclusion](#conclusion) With digital data growing at an incomprehensible rate, absorbing, storing, and analyzing data quickly while keeping your costs low can be difficult. So why not consider AWS Redshift? With its scalable, cloud-based architecture and powerful data warehousing capabilities, AWS Redshift allows you to manage and analyze large amounts of data quickly. And in this tutorial, you will get started with AWS Redshift and learn how it works, its features, benefits, and limitations. Sounds promising? Stay tuned and claim valuable insights that can help drive business decisions! ## Prerequisites This tutorial will be a hands-on demonstration. To follow along, be sure you have an [AWS account](https://repost.aws/knowledge-center/create-and-activate-aws-account) with an Amazon Simple Storage Service (S3) bucket. This tutorial uses an S3 bucket named _redshift-samp-data_ and [sample data files](https://docs.aws.amazon.com/redshift/latest/gsg/samples/tickitdb.zip) provided by AWS. Related:[How To Upload Files to S3 with the AWS CLI](https://adamtheautomator.com/upload-file-to-s3/) ## What is AWS Redshift? AWS Redshift is a cloud-based data warehousing service built to manage massive amounts of data quickly and efficiently. This service enables you to use your existing business intelligence tools and standard SQL to store and analyze your data. Another factor that makes Redshift stand out is that it costs less than any other cloud data warehouse. Performance-wise, AWS Redshift is one of the fastest data warehouses available. AWS Redshift enables quicker query times and more remarkable performance. How? By taking advantage of a massively parallel processing (MPP) architecture that spreads query processing across multiple nodes. ## Creating an IAM Role to Manage the AWS RedShift Service AWS Redshift data warehouse comprises a collection of computing nodes called a cluster. You will be creating a Redshift cluster, adding data to it, and also querying it. But since you will be loading the data from Amazon S3, you need an IAM role with the correct permissions. This IAM role will allow your cluster to communicate or interact with other Amazon services. To create an IAM role with the required privileges: Related:[Helpful Guide to IAM in AWS Through Examples](https://adamtheautomator.com/iam-aws/) 1\. Open your favorite web browser, and log in to your [AWS Management Console](https://console.aws.amazon.com/console). 2\. Next, search for **iam** and select **IAM** under **Services** from the search results, as shown below, to access the IAM dashboard. ![Accessing the IAM dashboard](https://adamtheautomator.com/wp-content/uploads/2023/01/image-286.png) Accessing the IAM dashboard 3\. On the IAM dashboard, click **Roles** (left panel) to access the page where you can manage roles. ![Accessing the Roles page](https://adamtheautomator.com/wp-content/uploads/2023/01/image-287.png) Accessing the Roles page 4\. Now, click **Create role** (upper-right) on the **Roles** page to initiate creating a role. ![Initiating creating a role](https://adamtheautomator.com/wp-content/uploads/2023/01/image-288.png) Initiating creating a role 5\. On the next page, select **AWS service** as the **Trusted entity type**. A trusted entity is an AWS service, application, or user who is trusted to take on an IAM role. ![Selecting the trusted entity type](https://adamtheautomator.com/wp-content/uploads/2023/01/image-289.png) Selecting the trusted entity type 6\. Next, scroll down and select **Redshift** in the dropdown field shown below, choose **Redshift – Customizable** option that appears below, and click **Next**. The **Redshift – Customizable** option allows AWS Redshift to access AWS services. ![Selecting Redshift as the use case](https://adamtheautomator.com/wp-content/uploads/2023/01/image-290.png) Selecting Redshift as the use case 7\. On the **Permissions policies** page, search for and tick the **[AmazonS3ReadOnlyAccess](https://docs.aws.amazon.com/AmazonS3/latest/userguide/security-iam-awsmanpol.html#security-iam-awsmanpol-amazons3readonlyaccess)** policy to select it, leave other default settings, and click **Next**. The **AmazonS3ReadOnlyAccess** policy provides read-only access to all your S3 buckets via the AWS Management Console. ![Selecting the read-only access policy](https://adamtheautomator.com/wp-content/uploads/2023/01/image-291.png) Selecting the read-only access policy 8\. Now, provide a unique name (i.e., **redshiftRole**) for the role. ![Providing Role details](https://adamtheautomator.com/wp-content/uploads/2023/01/image-292.png) Providing Role details 9\. Review the role details, and click **Create role** to finalize creating the role. ![Finalizing creating the Role](https://adamtheautomator.com/wp-content/uploads/2023/01/image-293.png) Finalizing creating the Role Once created, your browser redirects to the **Roles** page, where you will see the newly-created role, as shown below. ![Verifying the newly-created Role](https://adamtheautomator.com/wp-content/uploads/2023/01/image-294.png) Verifying the newly-created Role ## Creating an AWS Redshift Cluster Once you have created the IAM role, you are ready to create an AWS Redshift cluster. A Redshift cluster comprises nodes, each containing a set of processing power (CPU, memory, and storage) for storing and processing data. To create a Redshift cluster, follow these steps: 1\. In the AWS Management Console, search for **redshift** and select **Amazon Redshift** under **Services** in the search results. ![Searching for the AWS Redshift service](https://adamtheautomator.com/wp-content/uploads/2023/01/image-295.png) Searching for the AWS Redshift service 2\. Next, click **Create cluster** to initiate creating an AWS Redshift Cluster. ![Initiating creating an AWS Redshift Cluster](https://adamtheautomator.com/wp-content/uploads/2023/01/image-296.png) Initiating creating an AWS Redshift Cluster 3\. Provide a cluster name in the **Cluster identifier** field (i.e., **redshift-demo-cluster**), and choose whether you want to use this cluster for **Production** or **Free trial**. But this tutorial goes for Production. ![Enter cluster identifier](https://adamtheautomator.com/wp-content/uploads/2023/01/image-297.png) Enter cluster identifier 4\. Now, select **dc2.large** for the **Node type** and put **1** for the **Number of nodes**. Your choice of node type would depend on your workload requirements or factors, such as the complexity of your queries and data quantity. dc2.large is sufficient for this demonstration. ![Selecting the node type and number of nodes](https://adamtheautomator.com/wp-content/uploads/2023/01/image-298.png) Selecting the node type and number of nodes 5\. Under the **Database configurations** section, provide a database **Admin user name** and **password**. ![Providing an admin database username and password](https://adamtheautomator.com/wp-content/uploads/2023/01/image-299.png) Providing an admin database username and password 6\. Next, click **Associate IAM role,** which brings up a list of your IAM roles. ![Associating an IAM role](https://adamtheautomator.com/wp-content/uploads/2023/01/image-300.png) Associating an IAM role 7\. In the pop-up window, tick the checkbox beside the IAM role you created and click **Associate IAM roles** to add an associated IAM role. You will see the role listed as an associated role afterward. ![Adding an associated IAM role](https://adamtheautomator.com/wp-content/uploads/2023/01/image-301.png) Adding an associated IAM role 8\. Finally, scroll down to the **Additional configurations** section, leave the default settings, and click **Create cluster** to create your cluster. But if you choose not to use the defaults, you can make changes as follows: * Create a cloud watch alarm. Related:[How to Install and Set Up an AWS CloudWatch Agent](https://adamtheautomator.com/cloudwatch-agent/) * Change the database name and port. * Modify the backup and network settings, and so on. ![Creating the AWS Redshift cluster](https://adamtheautomator.com/wp-content/uploads/2023/01/image-302.png) Creating the AWS Redshift cluster Creating the cluster takes a few minutes, and you will see a success notification, as shown below, once the cluster is available for use. ![Verifying the cluster creation success](https://adamtheautomator.com/wp-content/uploads/2023/01/image-303.png) Verifying the cluster creation success ## Connecting to an AWS Redshift Cluster With an available AWS Redshift cluster, you can now test if the cluster works. Why? You will connect to your cluster using the Redshift Query Editor or other SQL client tools such as SQL Workbench. Related:[Getting Started With Mysql Workbench on Ubuntu Linux](https://adamtheautomator.com/mysql-workbench-on-ubuntu/) But in this tutorial, you will use the Redshift Query Editor, which provides a visual interface for creating and running SQL queries. Under the Clusters list, click on your cluster to access its details page. ![Accessing the newly-created cluster’s details page](https://adamtheautomator.com/wp-content/uploads/2023/01/image-304.png) Accessing the newly-created cluster’s details page Next, click on the **Query data** dropdown (upper-right) and select **Query editor v2** to open a connected query editor in a new tab. ![Opening a query editor](https://adamtheautomator.com/wp-content/uploads/2023/01/image-305.png) Opening a query editor Below, you can see the Redshift Query Editor v2. ![Exploring the Redshift Query Editor](https://adamtheautomator.com/wp-content/uploads/2023/01/image-306.png) Exploring the Redshift Query Editor ## Loading Data into AWS Redshift Cluster Before you can run queries or analyze data using AWS Redshift, you must load the data into the AWS Redshift cluster. In this example, you would load data into the AWS Redshift cluster from an AWS S3 bucket. This tutorial uses [sample data files](https://docs.aws.amazon.com/redshift/latest/gsg/samples/tickitdb.zip) provided by AWS. > 💡 O_nly S3, DynamoDB, and Amazon EMR permit simultaneous data uploads. If your data is housed in Amazon S3, relational DynamoDB, or Amazon EMR, Redshift can load your data efficiently using MPI. But for any other sources, parallel upload is not supported._ 1\. Navigate to your **Buckets** list, and click your S3 bucket (**redshift-samp-data**) to access it. ![Accessing the S3 bucket](https://adamtheautomator.com/wp-content/uploads/2023/01/image-307.png) Accessing the S3 bucket 2\. Next, click **Create folder** to initiate creating a folder in the bucket that will contain your data files. ![Initiating creating a folder in an S3 bucket](https://adamtheautomator.com/wp-content/uploads/2023/01/image-308.png) Initiating creating a folder in an S3 bucket 3\. Enter a name for the folder (i.e., _tickit-data-files_), and click **Create folder** to create the folder. ![Providing a folder name and creating the folder](https://adamtheautomator.com/wp-content/uploads/2023/01/image-309.png) Providing a folder name and creating the folder 4\. Now, click the folder name from the **Objects** table, as shown below, to navigate inside the folder. ![Accessing the newly-created folder](https://adamtheautomator.com/wp-content/uploads/2023/01/image-310.png) Accessing the newly-created folder 5\. In the folder’s **Objects** tab, click **Upload** to access the page where you can add data files to upload. ![Initiating uploading data files](https://adamtheautomator.com/wp-content/uploads/2023/01/image-311.png) Initiating uploading data files 6\. On the **Upload** page, click **Add files**, and locate your data files to upload to your S3 bucket. ![Adding data files to upload](https://adamtheautomator.com/wp-content/uploads/2023/01/image-312.png) Adding data files to upload 7\. Now, click **Upload** (bottom-right) to upload the selected data files to your folder. ![Uploading selected data files to the S3 bucket folder ](https://adamtheautomator.com/wp-content/uploads/2023/01/image-313.png) Uploading selected data files to the S3 bucket folder Once the upload completes, you will get a notification at the top of the page, like the one below. ![Verifying the upload is a success](https://adamtheautomator.com/wp-content/uploads/2023/01/image-314.png) Verifying the upload is a success ## Creating Tables via the Redshift Query Editor When inserting data from the files you uploaded to your S3 bucket, you first need to create tables. How? If you already have the Redshift Query Editor up, you are good to go. Run the following SQL statement in the query editor to create a table named `users`. ```sql create table users( userid integer not null distkey sortkey, username char(8), firstname varchar(30), lastname varchar(30), city varchar(30), state char(2), email varchar(100), phone char(14), likesports boolean, liketheatre boolean, likeconcerts boolean, likejazz boolean, likeclassical boolean, likeopera boolean, likerock boolean, likevegas boolean, likebroadway boolean, likemusicals boolean); ``` > 💡 _Note that the [Sort](https://docs.aws.amazon.com/redshift/latest/dg/t_Sorting_data.html) and [Di](https://docs.aws.amazon.com/redshift/latest/dg/c_best-practices-best-dist-key.html)[s](https://docs.aws.amazon.com/redshift/latest/dg/c_best-practices-best-dist-key.html)[t](https://docs.aws.amazon.com/redshift/latest/dg/c_best-practices-best-dist-key.html) keys must be thoroughly understood as they control how data is organized and indexed across all AWS Redshift nodes._ ![Creating the users table](https://adamtheautomator.com/wp-content/uploads/2023/01/image-315.png) Creating the users table You will see a summary of the execution at the bottom after running the statements. If any statement has a problem, an error message will be shown instead. ![Viewing the SQL statements execution summary](https://adamtheautomator.com/wp-content/uploads/2023/01/image-316.png) Viewing the SQL statements execution summary Now, run the rest of the SQL statements below to keep creating tables. ```sql create table venue( venueid smallint not null distkey sortkey, venuename varchar(100), venuecity varchar(30), venuestate char(2), venueseats integer); ``` ```sql create table category( catid smallint not null distkey sortkey, catgroup varchar(10), catname varchar(10), catdesc varchar(50)); ``` ```sql create table date( dateid smallint not null distkey sortkey, caldate date not null, day character(3) not null, week smallint not null, month character(5) not null, qtr character(5) not null, year smallint not null, holiday boolean default('N')); ``` ```sql create table event( eventid integer not null distkey, venueid smallint not null, catid smallint not null, dateid smallint not null sortkey, eventname varchar(200), starttime timestamp); ``` ```sql create table listing( listid integer not null distkey, sellerid integer not null, eventid integer not null, dateid smallint not null sortkey, numtickets smallint not null, priceperticket decimal(8,2), totalprice decimal(8,2), listtime timestamp); ``` ```sql create table sales( salesid integer not null, listid integer not null distkey, sellerid integer not null, buyerid integer not null, eventid integer not null, dateid smallint not null sortkey, qtysold smallint not null, pricepaid decimal(8,2), commission decimal(8,2), saletime timestamp); ``` ## Loading Data to Tables You now have your tables, but they are all practically empty. After creating the tables, you can load data from Amazon S3 by using the [`copy`](https://docs.aws.amazon.com/redshift/latest/dg/r_COPY.html) command. AWS Redshift integrates with many other AWS services, so you can quickly load data from sources such as Amazon S3 and Amazon DynamoDB. You can also analyze data using other services such as Amazon EMR and Amazon Athena. Below is the syntax of the `copy` command: ```bash copy table_name [ column_list ] FROM data_source CREDENTIALS access_credentials [options] ``` Run the following command to load the data from the `*allusers_pipe.txt*` file from your S3 bucket to your `users` table, replacing the following: * `` – Your [AWS account ID](https://docs.aws.amazon.com/IAM/latest/UserGuide/console_account-alias.html). * `` – The name of your IAM role. In this case, `redshiftRole`**.** * `us-west-2` – The region you set for your S3 bucket. * _`s3://redshift-samp-data/tickit-data-files` –_ The folder path in your S3 bucket. > 💡 _Suppose you are worried about data security; no need to be. AWS Redshift uses advanced encryption and security measures to protect your data._ ``` copy users from 's3://redshift-samp-data/tickit-data-files/allusers_pipe.txt' credentials 'aws_iam_role=arn:aws:iam:::role/' delimiter '|' region 'us-west-2'; ``` Now, repeat the same `copy` command to load data from the rest of the files, replacing `users` and `allusers_pipe.txt` with the corresponding table names and file names. ![Copying data from the S3 bucket to the tables in AWS Redshift](https://adamtheautomator.com/wp-content/uploads/2023/01/image-317.png) Copying data from the S3 bucket to the tables in AWS Redshift ## Querying a Cluster via the Redshift Query Editor Now that you have loaded some data into your cluster, you can use standard SQL queries to filter, sort, and aggregate the data. For example, you can use the `SELECT` statement to retrieve data from your tables, the `INSERT` statement to add new rows to a table, and so on. > 💡 _Note that AWS Redshift is designed for batch-style querying and may not be well-suited for applications that require low-latency queries or high levels of concurrency._ 1\. Run the following query in the editor to quickly return all (`*`) rows `FROM` the `users` table `WHERE` the `firstname` column has the value `Barry`. AWS Redshift offers data compression, which reduces storage requirements, thereby reducing disk I/O and improving query performance. When you execute a query, the compressed data is read into memory, then uncompressed during query execution. ``` SELECT * FROM users WHERE firstname = 'Barry'; ``` > 💡 _Redshift uses a columnar storage format, where data is organized into columns instead of rows. This behavior allows faster querying and analysis of data, as only the relevant columns need to be accessed and processed._ ![Querying users from a table ](https://adamtheautomator.com/wp-content/uploads/2023/01/image-318.png) Querying users from a table > 💡 _AWS Redshift provides result caching that stores the results of frequently executed queries in memory. As a result, the results can be quickly retrieved and returned to the user without recomputing. This feature improves query performance by reducing the amount of work that the database has to perform._ 2\. Next, run the below query to return the `sum` of all (`*`) the values in the `pricepaid` column `FROM` the `sales` table. ``` SELECT sum(pricepaid) FROM sales; ``` ![Querying the sum of values from a table column](https://adamtheautomator.com/wp-content/uploads/2023/01/image-319.png) Querying the sum of values from a table column 3\. Return to your cluster’s details page, and click the **Query monitoring** tab to view your query logs. ![Viewing the query logs](https://adamtheautomator.com/wp-content/uploads/2023/01/image-320.png) Viewing the query logs 4\. Now, scroll down to the **Queries and loads** section to view the queries you have performed so far, and click the number of the most recent query to view its execution details. The table presented should load your most recent query at the top. ![Viewing performed queries and load ](https://adamtheautomator.com/wp-content/uploads/2023/01/image-321.png) Viewing performed queries and load Your browser redirects to the **Query details,** where you can see what transpired in the query execution. ![Viewing the query details](https://adamtheautomator.com/wp-content/uploads/2023/01/image-322.png) Viewing the query details 5\. Lastly, click the **Query plan** tab → **Expand all** to see the actual steps and statistics for the query, and click any bar in the chart while scanning the diagram. Doing so lets you dig down into additional step specifics. Actual query statistics are provided in the **Execution timeline** and **Execution time** views, including the length of time taken by each query step. This data can be used for query optimization or debugging. The number of rows that the query would read or update in each step is shown in the **Text plan** view. You can also get performance metrics and the health status of the cluster. ![Viewing the steps and statistics of the query execution](https://adamtheautomator.com/wp-content/uploads/2023/01/image-323.png) Viewing the steps and statistics of the query execution ## Resizing an AWS Redshift Cluster Worried about messing up the infrastructure? AWS Redshift is a fully managed service, so you can quickly scale up or down without worrying about the underlying infrastructure. As your storage and performance needs fluctuate, you can resize a Redshift cluster. You may need to scale up to handle more data or complicated queries. Or perhaps scale down to cut costs when there is less demand for the cluster. But how? By adding or removing nodes. To resize an AWS Redshift cluster: 1\. Return to your cluster’s detail page, click the **Actions** dropdown, and click **Resize** to initiate resizing your cluster. ![](https://adamtheautomator.com/wp-content/uploads/2023/01/image-324-1024x444.png) 2\. Set the **Nodes** value to **2**, and click **Resize cluster** (bottom-right) to resize your cluster with one additional node. ![Resizing an AWS Redshift cluster](https://adamtheautomator.com/wp-content/uploads/2023/01/image-325.png) Resizing an AWS Redshift cluster A notification appears at the top, which indicates your cluster is being resized, while the **Status** section of your cluster indicates it is in a **Modifying** state. The process may take up to 15 or 20 minutes to resize and copy your data. Redshift terminates all connections during a resizing operation and restarts the original cluster in read-only mode. ![Viewing the resize progress ](https://adamtheautomator.com/wp-content/uploads/2023/01/image-326.png) Viewing the resize progress You can verify that the resize is complete when the cluster **Status** reads **Available**, as shown below. ![Confirming the cluster is running](https://adamtheautomator.com/wp-content/uploads/2023/01/image-327.png) Confirming the cluster is running ## Deleting an AWS Redshift Cluster Keeping unnecessary clusters only leads to unwanted charges. Why not clean your resources by deleting AWS Redshift clusters that are no longer needed? 1\. On your cluster’s details page, click the **Actions** dropdown and select **Delete** to delete the cluster. ![Deleting an AWS Redshift cluster](https://adamtheautomator.com/wp-content/uploads/2023/01/image-328.png) Deleting an AWS Redshift cluster 2\. In the form that pops up, under **Final snapshot**, untick the **Create final snapshot** box, type **Delete** in the field, and click **Delete cluster** to confirm deleting the cluster. ![Confirming the cluster deletion](https://adamtheautomator.com/wp-content/uploads/2023/01/image-329.png) Confirming the cluster deletion ![Verifying the cluster being deleted](https://adamtheautomator.com/wp-content/uploads/2023/01/image-330.png) Verifying the cluster being deleted ## Conclusion AWS Redshift is fast, reliable, and a great way to manage your data with various features. And this tutorial helped you get started with AWS Redshift by creating your first cluster and loading data to tables with the Redshift Query Editor. With this newfound knowledge, why not try loading and managing data to AWS Redshift with a third-party SQL tool, like [SQL Workbench/J](https://www.sql-workbench.eu/) and [pgAdmin](https://www.pgadmin.org/)? Related:[Installing the PGAdmin Ubuntu (PostgreSQL Dashboard)](https://adamtheautomator.com/pgadmin-ubuntu/) Share this article [Share on X](https://twitter.com/intent/tweet?url=https%3A%2F%2Fadamtheautomator.com%2Faws-redshift%2F&text=Getting%20Started%20with%20AWS%20Redshift)[Share on Facebook](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fadamtheautomator.com%2Faws-redshift%2F)[Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fadamtheautomator.com%2Faws-redshift%2F) ## Related Posts ![](https://adamtheautomator.com/wp-content/uploads/2026/08/featured_image-1.webp) ### [Survive the Senior Cloud Engineer AWS Interview Loop](/senior-cloud-engineer-interview-loop/) Prepare for a senior cloud engineer interview with AWS EKS and Control Tower system design reasoning, Terraform locking, and salary negotiation tactics. ![](https://adamtheautomator.com/wp-content/uploads/2026/02/featured_image-1-scaled.jpg) ### [Transition from SysAdmin to Cloud Engineer](/transition-sysadmin-cloud-engineer/) System administrators already have the networking, Linux, and operational expertise that cloud engineering demands. 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