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
Toad Data Point
Score 8.0 out of 10
N/A
Toad Data Point is a cross-platform, self-service, data-integration tool that simplifies data access, preparation and provisioning. It provides data connectivity and desktop data integration, and with the Workbook interface for business users, it provides simple-to-use visual query building and workflow automation.
$365
Pricing
RapidMiner
Toad Data Point
Editions & Modules
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
Base Edition
$365
Pro Edition
$528
Offerings
Pricing Offerings
RapidMiner
Toad Data Point
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
RapidMiner
Toad Data Point
Considered Both Products
RapidMiner
Verified User
Anonymous
Chose RapidMiner
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 …
For me, the best advantage to use RapidMiner is the ease of use to learn and deploy new processes. Yo don't need to code, you learn fast and it's really flexible when it comes to transforming data. Knime is also good, but not so flexible, and visually less attractive. Pentaho …
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual …
Used R and RapidMiner Studio. The main advantage for RapidMiner Studio is the reduced need to program. It has a much smaller learning curve, and it is easy to start using the tool and analyzing from day one.
We selected RapidMiner due to ease of use and a comfortable user interface. It stacks up very well against these tools in the predictive analytics space. For basic analytics and data reporting, we chose QlikView and Qlik Sense as a more robust reporting platform.
SPSS and SAS are too expensive. Their interfaces are excellent, but the price point is quite high making them inappropriate for higher education. KNIME is my second choice tool in this space, but it doesn't have the same long established english-speaking user community as …
The best part about RapidMiner is it mainly focus on machine learning algorithms whereas other tools focus on mainly the extract transform load (ETL) process. It can serve for all the KDD (Knowledge data discovery) process stages e.g. data cleaning, transformation, modeling and …
RapidMIner Studio is freely available and requires no programming skills. When compared with other free analytics tools, its graphical and analytical capabilities are far superior.
You simply cannot do everything with RapidMiner, it is just one tool in your arsenal. I like using Python directly much better with tools such as Jupyter Notebook in conjunction with JupyterHub.
The problem with R was that you had to code everything yourself and it doesn't do that well with large amounts of data. At the same time the advantage it provided was it has a large user base which means that you could get help easily.
TOAD excels at connecting to divergent data sources, but appears geared more to DBAs than to regular query users. Microsoft's offerings excel against Microsoft SQL Server, but sometimes struggle with other data sources.
However, SSMS and VS Code excel at many developer …
Both of these tools offer data extraction and even include SQL components. I noted earlier that RStudio is useful for statistical modeling and data visualization in ways Toad Data Point cannot do. Microsoft Access also has a useful query building window that Toad Data Point is …
I find Toad Data Point easy to use and easy to format and extract data to Excel. The Workbook (new interface) is closely tied to email. Intelligence Central is also closely tied to email. I find this tool essential if your data is stored in different database types or some …
Toad give me more flexibility. Being able to utilize FTP to send data and receive files from external systems is wonderful. Using the automation tool to run different database, file, and system activities has made my day-to-day functions easy. Being able to schedule tasks …
We have tried to use Tableau to try and accomplish a similar set of goals as we do with Toad Data Point. Toad is much more efficient once we have the data connections setup. We are able to easily drag and drop data sources. There are some advantages with Tableau but overall …
I have not used another tool that allows for these seamless connections so it is unfair to rate Tableau and Hyperion against this becuase they have different uses. But if I had to compare, Tableau does not make it as easy to connect to multiple datasources and definitely has …
RapidMiner is the best tool to build models on textual data. It is rich in ML algorithms and reduces the need to manually tune the parameters. It automatically optimizes them, thus providing a better solution. RapidMiner again extends great capability for data preparation, its insane connections to almost every data source pulls in the data easily into one environment. And it can comfortably perform data cleaning and process tasks over that. RapidMiner is not so good with image, audio or video data. These data points cannot be used directly in their raw form. They must be transformed into some intermediate form for performing analytics over it. Moreover, there are no connectors to directly pull data from their varied sources. For example, we don't have a connector to read audio data directly from a switch and then convert it to text (although Google speech API is available for audio to text conversion.)
Toad Data Point is the clear tool of choice if the end-user is interested in reports that are relatively simple to build using SQL code and export to Excel. It is less useful if the analyst also needs to run statistical models on the data and visualize the data for those functions I usually use RStudio or Jupyter Notebook which incorporates those features much more seamlessly.
Wish the tool was more efficient in terms of processing power. The tool takes a lot of CPU processing power, even for a small process on a small data set
Wish there were more options on charts and graphs to visualize the data
I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual workflow and therefore it is easier to demonstrate and visualise the processes involves in getting the desired results. Visualization of workflow enhances teaching and learning. RapidMiner is rich with algorithms and online learning materials that can assist students in their self-directed learning on data preparation, machine learning, deep learning, text mining, and predictive analytics. Moreover, RapidMiner repository has more than 1500 machine learning algorithms and functions that students can explore for any case study and assignments. The RapidMIner is also an open platform that can seamlessly integrates with other applications programmed with other programming languages like R and Python.
TOAD excels at connecting to divergent data sources, but appears geared more to DBAs than to regular query users. Microsoft's offerings excel against Microsoft SQL Server, but sometimes struggle with other data sources. However, SSMS and vs code excel at many developer productivity/workflow enhancements. vs code, in particular, has a lively extension system that allows it to be tailored for development/querying/model building/etc. That flexibility comes at a cost - the learning curve is steep for new users. The tradeoff between complexity and power may not be good for some environments/users/situations.
It is the least common denominator - not particularly optimized for our environment or workflows.
Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.