Overview
At KNIME, we build software to create and productionize data science using one easy and intuitive environment, enabling every stakeholder in the data science process to focus on what they do best.
KNIME Analytics Platform is the open source software for creating data science. KNIME Server is the enterprise software for team-based collaboration, automation, management, and deployment of data science workflows as analytical applications and services. Non experts are given access to data science via KNIME WebPortal or can use REST APIs to integrate workflows as analytical services to applications.
KNIME Software for AWS provides a best-in-class solution for building and governing end to end data analytics and machine learning pipelines. Enterprises across all sectors are collecting and storing vast amounts of data in order to make better decisions, but few are realizing its full potential. KNIME for AWS allows one open platform to extract and transform this data into something useful, analyze the data using the most modern data science techniques, incorporate existing ML software, services and capabilities, deploy models or algorithms to any application or visualization endpoint, and complete this entire process in the context of a highly secure, scalable, auditable, and reusable fashion. KNIME Server for AWS brings together the many creators, contributors, and users of analytics and ML within the organization in a visual environment that speeds up comprehension and decision
Highlights
- Shared repository for KNIME Workflows, components, models, and data
- Web application services for Guided Analytics
- RESTful web services ready and scheduled execution
Details
Typical total price
$5.074/hour
Features and programs
Financing for AWS Marketplace purchases
Pricing
- ...
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t2.medium | $4.57 | $0.046 | $4.616 |
t2.large | $4.57 | $0.093 | $4.663 |
t2.xlarge | $4.57 | $0.186 | $4.756 |
t2.2xlarge | $4.57 | $0.371 | $4.941 |
t3.large | $4.57 | $0.083 | $4.653 |
t3.xlarge | $4.57 | $0.166 | $4.736 |
t3.2xlarge | $4.57 | $0.333 | $4.903 |
t3a.large | $4.57 | $0.075 | $4.645 |
t3a.xlarge | $4.57 | $0.15 | $4.72 |
t3a.2xlarge | $4.57 | $0.301 | $4.871 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp2) volumes | $0.10/per GB/month of provisioned storage |
Vendor refund policy
We do not currently support refunds, but you can cancel at any time.
Legal
Vendor terms and conditions
Content disclaimer
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
Update to KNIME Server 4.16.9 and KNIME Executor 5.2.2. Including Workflows as a Service, dynamic Data Apps, and several new connectors.
Additional details
Usage instructions
Access the application via a browser at http://<public_dns>/knime, or https://<public_dns>/knime. Admin username is: knimeadmin and password is the AWS instance ID. To connect to the operating system, use SSH and the username ubuntu. The KNIME Server is controlled via a systemd process named 'knime-server.service'. All KNIME Server related files can be found in /opt and /srv. Files and directories are owned by the user 'knime'. AWS Specific Documentation is found at: User data is stored on a block device mounted under /srv. The KNIME Server can be stopped by running sudo systemctl stop knime-server.service. Use the volume ID to mount the volume with your existing data onto the new instance. Full details can be found at: https://docs.knime.com/latest/aws_marketplace_server_guide/index.html Full documentation is available in the KNIME Server Administration Guide: https://docs.knime.com/latest/server_admin_guide/index.html
Resources
Vendor resources
Support
Vendor support
Register your KNIME marketplace product for support 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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Customer reviews
I think best software ever for data analytics and machine learning
Easy to understand, Variety of Nodes
KNIME is the best software to automate accounting processes
Is the best alternative to Alteryx.
Knime is The Future : Data Engineers Pay attention
As I am attending the Knime conference and finishing up the first (L1) workshop, the session is ending and yet it is seems like I can continue to hear the instructor what is here, what is going to happen and what shall happen.
I can use it for simple task to replace excel, or run large AI models. I completed my dissertation work with KNIME about 4 years ago; Knime helped me then, and it continues to help me now. I use it for developing and running models, or to teach business intelligence. Sometimes I just use it showoff :).
I know the question is what I like best about the software, yet I could not hold my excitement to write above. I like the point and click workflow, the plethora of nodes, nodes that connect with other languages, and yes if you are data wrangler, I would say Knime is the best data engineering platform. And Yes now, checkout their Visual nodes, report generator, and if you are still shy of getting on AI bandwagon, try the GEN AI tools; Just search on Knime.com.
No code, easy to use and easy to innovate
Easy to learn and start delivering.
Great integration with powerful programming languages (Python, Java) .
One stop shop for production ready Data Engineering/Data Analytics and Data Science solutions.
Compatibility check for workflows between Client and Server versions can be great for development.
A bit spacious UI for the client application would be appreciated.
No code ETL process (easy to learn) .
Cheaper solution compared to alternatives.
One stop analytical application for integrating ETL, modelling and reporting.