Sold by: Code Creator
Deployed on AWS
AWS Free Tier
Launch Apache Superset on AWS in minutes with pre-configured Athena, Redshift, Aurora Data API, Snowflake, PostgreSQL, MySQL, and Trino connectors.
Overview
Apache Superset Ready-to-Launch Analytics on AWS
Code Creator Advanced Analytics Server delivers Apache Superset as a fully provisioned, production-ready analytics stack that launches directly in your AWS account. Skip the hours of manual configuration - this AMI handles the entire setup on first boot so your team can start exploring data in minutes.
Automated First-Boot Provisioning
When you launch the instance, the AMI automatically:
- Generates unique application, database, cache, and administrator credentials
- Initializes PostgreSQL metadata storage
- Configures authenticated Valkey caching
- Starts the Superset web application, Celery workers, task scheduler, and Nginx web endpoint
A secure local FIRST LOGIN.txt file on the EC2 instance provides the administrator with the initial URL and generated login credentials, so you can log in immediately.
Use Case: Connect Your Data Warehouse and Build Executive Dashboards
A common workflow after deployment is connecting to your existing data warehouse - such as Amazon Redshift or Amazon Athena - and building interactive KPI dashboards for business stakeholders. Analysts use SQL Lab to write and validate queries against live data, then transform results into charts and publish them as shared dashboards. With preinstalled drivers for Amazon Athena, Amazon Redshift, Amazon Aurora Data API, Snowflake, PostgreSQL, MySQL, and Trino, your team can query across multiple sources without installing additional packages. Business users can also build charts without writing code, define reusable metrics and dimensions, and schedule automated reports via the built-in alerts and reports framework by configuring their own SMTP or Slack delivery settings.
Security-Focused Architecture
This deployment is designed with deliberate security practices:
- Network isolation: PostgreSQL, Valkey, and the Superset application port run on internal Docker networks that are not exposed to external traffic
- Minimal attack surface: Only SSH and the Nginx web endpoint are intended for EC2 security-group access
- Unique credentials per instance: Every deployment generates its own set of application, database, cache, and admin credentials, eliminating shared default passwords
- Customer-controlled TLS: Customers retain full control of their TLS certificates, allowing you to apply your organization's certificate management policies to the Nginx endpoint
- Full infrastructure ownership: You retain control of your AWS account, EC2 instance, network rules, data sources, backups, and operating costs
Operational Management Tooling
The included cc superset management command gives administrators a single interface for day-to-day operations:
- Status and health checks - Verify all components are running correctly
- Restart and recovery - Restart individual services or the full stack
- Log access - View logs across Superset, Celery, PostgreSQL, Valkey, and Nginx
- Version reporting - Confirm deployed software versions
- Full-stack validation - Run comprehensive health checks across all components
About Apache Superset
Apache Superset is an open-source data exploration and visualization platform capable of handling data at petabyte scale. Originally created at Airbnb, it graduated to a top-level project at the Apache Software Foundation in 2021 and has received significant contributions from leading technology companies including Lyft and Dropbox.
Get Started
Launch the AMI from AWS Marketplace, wait for first-boot provisioning to complete, and retrieve your credentials from the FIRST LOGIN.txt file on the instance. Your analytics server will be ready for data connections and dashboard creation within minutes of launch.
Highlights
- Secure by default with unique credentials on every launch: Unlike a standard Superset installation that ships with shared default passwords, this AMI generates unique application, database, cache, and administrator credentials directly on your instance during first boot. Each deployment receives its own secrets, eliminating the risk of running production workloads on well-known default credentials. Credentials are stored in a FIRST LOGIN.txt file accessible only from the instance itself.
- Production-integrated analytics stack requiring no manual assembly: Deploys Apache Superset 6.1.0 with PostgreSQL metadata storage, authenticated Valkey caching, Nginx reverse proxy, and Celery workers and scheduler as a coordinated stack. PostgreSQL, Valkey, and the Superset application port run on internal Docker networks, reducing your attack surface without manual firewall configuration.
- Pre-installed connectors for AWS and modern data platforms: Includes ready-to-use drivers for Amazon Athena, Amazon Redshift, Amazon Aurora Data API, Snowflake, PostgreSQL, MySQL, and Trino. Analysts and business users can explore data in SQL Lab, build charts without code, and connect to your existing data sources immediately after launch without installing additional Python packages or resolving driver dependencies.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t3.large Recommended | $0.025 |
t3.micro | $0.025 |
t2.micro | $0.025 |
g5.8xlarge | $0.025 |
d2.8xlarge | $0.025 |
t3a.small | $0.025 |
i3en.3xlarge | $0.025 |
c5d.4xlarge | $0.025 |
m5dn.4xlarge | $0.025 |
c6i.xlarge | $0.025 |
Dimensions summary
You pay by the hour for this Apache Superset server, billed only while your instance runs. Each dimension maps to a specific AWS EC2 instance type, so pricing scales with the compute size you pick. Smaller instances like t2.nano or t3.micro cost less per hour than large ones like u-24tb1.metal or p4d.24xlarge. The software runs on the same image across all sizes; the hourly rate reflects the CPU, memory, storage, and GPU capacity of the instance you choose. Pick the size that matches your workload, then scale up or down by switching instance types.
Top-of-mind questions for buyers
You get a pre-built Apache Superset server running on the AWS EC2 instance size you select. The rate combines the software license and the compute resources of that instance, such as its CPU, memory, storage, and any GPU. The image is provisioned and ready to deploy.
The software charge meters running instance-hours only. When you stop the instance, the hourly software charge stops accruing. Stopped instances may still incur underlying AWS storage fees for attached volumes, but those are separate AWS charges, not part of this software license.
Switch to a different instance type from the list. The software runs on the same image across all sizes, so you keep the same product. Your hourly rate then matches the new instance you picked. You are billed at each instance's rate only while that instance runs.
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Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Apache Superset on Ubuntu 26.04 LTS with automated first boot setup, PostgreSQL metadata storage, Valkey caching, Nginx, Celery workers, Playwright support, and preinstalled connectivity for Athena, Redshift, Snowflake, PostgreSQL, MySQL, Aurora Data API, and Trino.
Additional details
Resources
Vendor resources
Support
Vendor support
For support inquiries related to the Apache Superset Advanced Analytics Server AMI by Code Creator, contact the team via email at info@codecreator.com .
When submitting a support request, please include your EC2 instance ID, the AWS region where the instance is running, and a description of the issue you are experiencing. This helps the team diagnose and resolve your issue more efficiently.
For general Apache Superset usage guidance, the upstream project documentation is available at https://superset.apache.org/user-docs/ and the community resources are available at
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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AI generated from product descriptions
Analytics and Visualization Engine
Apache Superset 6.1.0 with SQL Lab for data exploration, code-free chart building, reusable metrics and dimensions definition, and interactive dashboard publishing capabilities.
Database Connectivity
Pre-installed drivers for Amazon Athena, Amazon Redshift, Amazon Aurora Data API, Snowflake, PostgreSQL, MySQL, and Trino database connectivity.
Caching and Task Processing
Authenticated Valkey caching layer integrated with Celery workers and task scheduler for asynchronous job processing and performance optimization.
Metadata Storage and Web Server
PostgreSQL metadata storage with Nginx web endpoint configuration and automated credential generation for secure application deployment.
Operational Management and Health Validation
Operational health checks and cc-superset management command for status reporting, health validation, restart capabilities, logs access, version reporting, and full-stack validation.
Container Orchestration
Docker-based deployment architecture enabling simplified deployment and upgrade processes
One-Click Application Deployment
Support for one-click deployment of over 200 template applications from integrated console
Multi-Application Management
Console panel for installing and managing multiple applications on a single instance
GitOps Deployment Approach
GitOps-based deployment methodology with continuous deployment capabilities for live applications
Web-Based Administration Interface
Web-based console for domain binding, HTTPS configuration, access control, and status monitoring
Semantic Layer Architecture
Built-in semantic model that provides governed metrics and ensures consistency across analytics queries and AI-generated answers
Conversational AI Analytics
Natural language processing capability enabling users to ask AI questions and receive trusted answers without requiring SQL knowledge
Git Integration and Version Control
Git-based integration with branching, content validation, and version history for managing changes to semantic models and analytics content
Excel Workflow Integration
Native Excel spreadsheet compatibility allowing users to perform financial modeling, forecasting, and exploratory analysis within the platform
Software Development Lifecycle Features
CICD pipeline support, content validation, and developer workflows for safely testing and deploying model changes across environments
Standard contract
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