Sold by: EASYCLOUD
Deployed on AWS
AWS Free Tier
This product has charges associated with it for technical support with a 24-hour response time. This AMI contains DuckDB and a Python Data Science stack on Ubuntu 24.04 LTS repackaged by Easycloud, fully configured for production environments. The system is built on a minimal installation of Ubuntu, updated to the latest version, and includes continuous updates and support to ensure a secure foundation.
Overview
This is a repackaged open source software product wherein additional charges apply for technical support with a 24-hour response time. DuckDB 1.4, Pandas, and NumPy, built on a minimal Ubuntu 24.04 installation, are included in this AMI, repackaged by Easycloud. It provides a complete, pre-configured analytical data stack, deliberately engineered to enable high-performance OLAP workloads and data science workflows without setup overhead.
Core Features & Integrations
- Ubuntu 24.04 LTS Minimal: A renowned Linux distribution celebrated for its exceptional stability, vast software repository, and strict adherence to open-source principles. As the world's most widely deployed cloud Linux OS and the direct downstream of Debian, it provides unparalleled ecosystem compatibility while delivering a clean, bloat-free, and secure enterprise-grade core.
Key Benefits
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Enterprise-Grade Virtual Environment: Python and data science libraries are installed in a dedicated, globally accessible virtual environment (/opt/duckdb-env), ensuring zero conflict with the core Ubuntu system Python.
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Seamless Integration: Global path variables are pre-configured (/etc/profile.d/duckdb_env.sh), allowing all users to access the data science stack immediately upon login without manual environment activation.
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Out-of-the-box Analytics: Pre-installed with DuckDB, Pandas, and NumPy, bypassing complex setup procedures and allowing you to query and analyze data instantly.
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Secure Foundation: Built on a hardened Ubuntu base with the latest security patches applied for enterprise-grade reliability.
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The Optimal High-Performance Analytics and Data Science Foundation: By starting with a bloat-free Ubuntu 24.04 base, every CPU cycle and memory byte is dedicated entirely to the DuckDB engine and its Python analytics stack. This makes it the perfect, conflict-free foundation for in-process OLAP workloads, batch analytics, and data science pipelines powered by the Python ecosystem (Python, PyTorch, SQLAlchemy). It integrates natively with leading BI and visualization platforms (Grafana, Metabase, Apache Superset, Kibana), pairs seamlessly with relational and time-series backends (PostgreSQL, MySQL, InfluxDB), and provides a robust analytical layer alongside major big-data and streaming engines (Apache Spark, Apache Kafka, Apache Flink, Apache Zookeeper). It also slots directly into ML lifecycle platforms (MLflow), log aggregation pipelines (Logstash, Prometheus, OpenSearch), and containerized analytical infrastructure (Docker, ClickHouse), ensuring your analytics environment scales without limits.
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Production Ready & Expert Support: Secured with the latest OS patches. It delivers a highly stable environment, fully supported by comprehensive documentation and fast technical assistance (guaranteed 24-hour response time) to ensure your infrastructure runs smoothly without costly downtime.
Highlights
- DuckDB 1.4: Best-practice deployment.
- Ubuntu 24.04 (Minimal Installation), updated to the latest version.
- Expert Support: Backed by comprehensive documentation and fast, professional technical assistance.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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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.medium Recommended | $0.01 |
t3.micro | $0.01 |
t2.micro | $0.01 |
m7i-flex.12xlarge | $0.09 |
m5.24xlarge | $0.09 |
i7ie.48xlarge | $0.09 |
r5a.large | $0.01 |
m7i.metal-24xl | $0.09 |
r5a.8xlarge | $0.09 |
m6id.2xlarge | $0.05 |
Dimensions summary
You pay by the hour for the EC2 instance type you run this DuckDB image on. Each dimension maps to one AWS instance size, and the software rate scales with the instance you choose. Smaller general-purpose instances cost less per hour, while memory-optimized, compute-optimized, storage-optimized, and accelerated instances carry higher rates. There is no upfront commitment or fixed term. You start and stop instances as needed, so total cost depends on which instance you pick and how many hours you run it. Choose the size that fits your workload's memory and compute needs.
Top-of-mind questions for buyers
You get Ubuntu 24.04 LTS with DuckDB 1.4.4 pre-installed in an isolated Python 3.12 virtual environment at /opt/duckdb-env. Pandas and NumPy are included for data analysis. The environment activates automatically for all users at login, so no manual setup is needed.
The hourly software rate meters running time only. A stopped instance does not accrue the software charge. You may still pay underlying AWS fees for attached storage while the instance is stopped, but the DuckDB software charge stops when the instance is not running.
Yes. Each dimension maps to one EC2 instance type, and the software rate is set per instance size. Larger memory-optimized, compute-optimized, or accelerated instances carry higher hourly software rates than smaller general-purpose ones. Your total also depends on how many hours you run.
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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
Latest Updates
Additional details
Usage instructions
Connection Methods
To access your instance, SSH into the public IP address as 'ubuntu' using your specified launch key pair. You can switch to the root user environment by running sudo su -. Please see the links below for additional information:
Install Information
Operating System: Ubuntu 24.04 LTS
DuckDB Version: 1.4.4
Python Version: 3.12
Virtual Environment Location: /opt/duckdb-env
Activation Command: source /opt/duckdb-env/bin/activate
Environment Configuration: /etc/profile.d/duckdb_env.sh
Python Binary Path: /opt/duckdb-env/bin/python
pip Binary Path: /opt/duckdb-env/bin/pip
Quick Verification Commands
Check Python path by running: which python
Check DuckDB version by running: pip show duckdb | grep Version
Check Pandas version by running: pip show pandas | grep Version
Check NumPy version by running: pip show numpy | grep Version
Firewall Configuration
SSH (Port 22): Required for initial system access.Security Recommendation: Strictly limit SSH access to trusted IP addresses only via AWS Security Groups.
Documentation
For a detailed installation and management guide, please visit: https://www.easyclouds.io/docs/duckdb-guide
Resources
Vendor resources
Support
Vendor support
Should you encounter any issues while using the system, please do not hesitate to contact us via email at: support@easyclouds.io . Thank you!
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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