Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing services. With over 165 services offered, AWS services can provide users with a comprehensive suite of infrastructure and computing building blocks and tools.
$100
per month
RapidMiner
Score 8.9 out of 10
N/A
RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
$7,500
Per User Per Month
Pricing
Amazon Web Services
RapidMiner
Editions & Modules
Free Tier
$0
per month
Basic Environment
$100 - $200
per month
Intermediate Environment
$250 - $600
per month
Advanced Environment
$600-$2500
per month
Professional
$7,500.00
Per User Per Month
Enterprise
$15,000.00
Per User Per Month
AI Hub
$54,000.00
Per User Per Month
Offerings
Pricing Offerings
Amazon Web Services
RapidMiner
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
AWS allows a “save when you commit” option that offers lower prices when you sign up for a 1- or 3- year term that includes an AWS service or category of services.
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More Pricing Information
Community Pulse
Amazon Web Services
RapidMiner
Features
Amazon Web Services
RapidMiner
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Amazon Web Services
8.4
78 Ratings
2% above category average
RapidMiner
-
Ratings
Service-level Agreement (SLA) uptime
9.072 Ratings
00 Ratings
Dynamic scaling
8.873 Ratings
00 Ratings
Elastic load balancing
9.369 Ratings
00 Ratings
Pre-configured templates
7.166 Ratings
00 Ratings
Monitoring tools
8.473 Ratings
00 Ratings
Pre-defined machine images
8.366 Ratings
00 Ratings
Operating system support
7.972 Ratings
00 Ratings
Security controls
8.674 Ratings
00 Ratings
Automation
8.325 Ratings
00 Ratings
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Amazon Web Services
-
Ratings
RapidMiner
9.5
2 Ratings
13% above category average
Connect to Multiple Data Sources
00 Ratings
10.02 Ratings
Extend Existing Data Sources
00 Ratings
10.02 Ratings
Automatic Data Format Detection
00 Ratings
9.02 Ratings
MDM Integration
00 Ratings
9.01 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Amazon Web Services
-
Ratings
RapidMiner
9.0
2 Ratings
6% above category average
Visualization
00 Ratings
9.02 Ratings
Interactive Data Analysis
00 Ratings
9.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Amazon Web Services
-
Ratings
RapidMiner
8.8
2 Ratings
8% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
9.02 Ratings
Data Transformations
00 Ratings
7.02 Ratings
Data Encryption
00 Ratings
9.02 Ratings
Built-in Processors
00 Ratings
10.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Amazon Web Services
-
Ratings
RapidMiner
9.0
2 Ratings
7% above category average
Multiple Model Development Languages and Tools
00 Ratings
9.02 Ratings
Automated Machine Learning
00 Ratings
9.02 Ratings
Single platform for multiple model development
00 Ratings
9.02 Ratings
Self-Service Model Delivery
00 Ratings
9.02 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
This is something that is actually common across most cloud providers. A comprehensive understanding of one's use cases, constraints and future directions is key to determining if you even need a cloud solution. If you are a 2-person startup developing something with a best-scenario audience of 1k DAU in a year, you would very likely best served by a dirt-cheap dedicated Linux server somewhere (and your options to graduate to a cloud solution will still be open). If, however, you are a bigger fish, and/or you are actively considering build-vs-buy decisions for complicated, highly-loaded, six-figure requests per minute systems, global loadbalancing, extreme growth projections - then MAYBE you solve all or part of it with a cloud provider. And depending on your taste for risk, reliability, flexibility, track record - it might be AWS.
RapidMiner is really fantastic to perform fast ETL processes and work on your data as you want, no matter what is the source. You will really save a lot of time when you learn how to use it. You can create mining analysis with several algorithms, and thanks to add-ons, you can apply a lot of techniques. It will not replace a business intelligence dashboard but it allows to create great datamarts for your BI tools. One negative thing is that It's no easy to share your outputs.
I am very impressed at how easily you can work within RapidMiner without much data analytics training. Plus with the help of the crowd, you can see what steps others have taken with their data analytics projects.
Text mining was simple and clean. We used this for our call transcription problem where we didn't have the resources to listen to each call. We needed to qualify each call based on some key phrases.
Our direct mail program was large and not very targeted. Using RapidMiner, we were able to isolate a predictive level we felt comfortable with and decided not to send to anyone below that level. We saved quite a bit of money.
I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates.
Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model.
More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples.
We are almost entirely satisfied with the service. In order to move off it, we'd have to build for ourselves many of the services that AWS provides and the cost would be prohibitive. Although there are cost savings and security benefits to returning to the colo facility, we could never afford to do it, and we'd hate to give up the innovation and constant cycle of new features that AWS gives us.
AWS offers a wide range of powerful services that cater to various business needs which is significant strength. The ability to scale resources on-demand is a major advantage making it suitable for businesses of all sizes. The sheer volume of options and configurations can be overwhelming for new users leading to a steep learning curve. While functional the AWS management console can feel cluttered and less intuitive compared to some competitors which can hinder navigation. Although some documentation lacks clarity and practical examples which can frustrate users trying to implement specific solutions.
AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.
The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to immediately search for their compatible software's and also to guide them in a good direction. Moreover, this product is a good suggestion for every type of company because of its affordability and ease of use.
Amazon Web Services fits best for all levels of organisations like startup, mid level or enterprise. The services are easy to use and doesn't require a high level of understanding as you can learn via blogs or youtube videos. AWS is Reasonable in cost as the plan is pay as you use.
We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and user-friendly.
Using Amazon Web Services has allowed us to develop and deploy new SAAS solutions quicker than we did when we used traditional web hosting. This has allowed us to grow our service offerings to clients and also add more value to our existing services.
Having AWS deployed has also allowed our development team to focus on delivering high-quality software without worrying about whether our servers will be able to handle the demand. Since AWS allows you to adjust your server needs based on demand, we can easily assign a faster server instance to ease and improve service without the client even knowing what we did.
Thanks to the patters that RapidMiner has detected, we have been able to follow clues in the right direction, both for the Protein Interaction Network Analysis and for the Epilepsy Research
Students and participants of the machine learning workshops have learned about this technology and about the tool