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Compare Altair AI Studio and TIMi 
At a Glance
Market Segments
Small-Business (42.6% of reviews)
Small-Business (37.5% of reviews)
Entry-Level Pricing
No pricing available
Free
Altair AI Studio
Star Rating
(505)4.6 out of 5
Market Segments
Small-Business (42.6% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Altair AI StudioTIMi
Star Rating
(70)4.9 out of 5
Market Segments
Small-Business (37.5% of reviews)
Entry-Level Pricing
Free
Free Trial is available
Browse all 5 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Altair AI Studio excels in its "Data Preparation" capabilities, particularly with its "Data Ingestion & Wrangling" feature, which received a score of 8.6. In contrast, TIMi Suite shines with a score of 9.0 in the same area, indicating a more robust and user-friendly experience for data handling.
- Reviewers mention that TIMi Suite offers superior "Model Training" features, scoring 9.5 compared to Altair AI Studio's 8.4. This difference highlights TIMi's advanced capabilities in training AI models, making it a preferred choice for users focused on machine learning.
- G2 users indicate that TIMi Suite's "Quality of Support" is notably higher at 9.3, while Altair AI Studio scores 8.5. This suggests that users of TIMi Suite may experience more responsive and effective customer service, which is crucial for troubleshooting and guidance.
- Users on G2 report that Altair AI Studio's "Reports Interface" is less intuitive, scoring only 8.0, while TIMi Suite does not have a specific score listed but is generally perceived as having a more user-friendly reporting system, enhancing the overall user experience.
- Reviewers mention that TIMi Suite's "Data Visualization" capabilities are rated at 8.8, which is higher than Altair AI Studio's 8.7. This indicates that TIMi Suite may provide more effective tools for visualizing data, which is essential for data analysis and presentation.
- Users say that both products offer "Drag and Drop" functionality, scoring equally at 9.2, which is a significant feature for ease of use. However, TIMi Suite's overall higher ratings in other areas suggest a more comprehensive user experience despite similar functionality in this aspect.
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Pricing
Entry-Level Pricing
Altair AI Studio
No pricing availableTIMi
Community
Free
The whole TIMi Suite is 100% free for:
- “Startup Companies” (less than 500K€ of revenues), to bootstrap their activities
- Charity Companies, NGO’s, humanitarian companies
- Any consulting company engaged in charity or humanitarian work
Free Trial
Altair AI Studio
Free Trial is available
TIMi
Free Trial is available
Ratings
Meets Requirements
8.6
419
9.4
53
Ease of Use
8.8
418
9.1
51
Ease of Setup
9.0
121
9.2
22
Ease of Admin
8.4
104
8.5
18
Quality of Support
8.5
348
9.3
51
Has the product been a good partner in doing business?
8.9
93
9.4
19
Product Direction (% positive)
8.8
405
9.5
45
Features by Category
Reports
Not enough data
8.0
18
Not enough data
8.8
23
Not enough data
8.3
21
Not enough data
8.4
16
Not enough data
7.9
19
Data Preparation
Not enough data
9.6
24
Not enough data
Feature Not Available
Data Modeling and Blending
Not enough data
9.3
25
Not enough data
9.3
25
Not enough data
9.4
26
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Self Service
Not enough data
9.5
26
Not enough data
9.6
24
Not enough data
9.3
27
Not enough data
9.3
24
Not enough data
8.9
19
Not enough data
Feature Not Available
Deployment & Integration - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics
Not enough data
9.3
27
Not enough data
8.7
20
Not enough data
9.2
24
Performance & Scalability - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Capabilities - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Personalized Intelligence - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Building Reports
Not enough data
9.2
22
Not enough data
9.2
21
Not enough data
7.6
13
Not enough data
8.3
18
Data Source Access
Not enough data
9.4
27
Not enough data
9.4
26
Not enough data
8.7
18
Data Interaction
Not enough data
8.8
20
Not enough data
9.2
21
Not enough data
9.4
24
Not enough data
9.4
26
Not enough data
9.3
25
Not enough data
9.4
26
Not enough data
9.0
20
Not enough data
8.9
21
Data Exporting
Not enough data
8.9
23
Not enough data
9.0
24
Not enough data
9.2
24
Generative AI
Not enough data
Not enough data
Administration
Not enough data
9.4
13
Not enough data
9.0
12
Not enough data
8.8
8
Capabilities
Not enough data
8.8
8
Not enough data
9.0
8
Not enough data
8.6
7
Not enough data
9.1
9
Methodology
Not enough data
8.0
10
Not enough data
8.6
12
Not enough data
8.2
10
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
8.5
51
9.0
12
8.0
28
8.8
12
9.2
49
9.2
13
Model Development
7.6
32
8.6
12
9.1
56
9.1
13
8.5
53
9.2
13
8.4
51
9.5
14
Model Development
8.8
52
9.2
13
8.5
48
9.2
12
8.4
46
8.9
12
Machine/Deep Learning Services
7.6
29
Feature Not Available
7.8
34
8.7
10
7.4
22
Feature Not Available
8.4
38
9.1
9
Machine/Deep Learning Services
7.8
25
Feature Not Available
7.5
31
9.0
7
7.4
24
8.8
7
8.3
35
9.3
7
Deployment
7.9
37
8.8
10
8.3
36
8.9
11
8.4
33
9.5
14
Deployment
8.2
30
8.5
9
8.3
32
8.6
11
8.6
29
9.2
11
Generative AI
6.7
6
Not enough data
6.7
6
Not enough data
6.4
6
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Setup
8.0
5
Not enough data
7.7
5
Not enough data
8.3
5
Not enough data
Data
8.0
5
Not enough data
8.3
5
Not enough data
Analysis
8.3
5
Not enough data
7.3
5
Not enough data
7.3
5
Not enough data
7.0
5
Not enough data
7.0
5
Not enough data
7.0
5
Not enough data
6.0
5
Not enough data
Customization
8.3
5
Not enough data
8.7
5
Not enough data
8.0
5
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
7.9
176
9.2
16
8.9
249
9.3
17
8.6
266
9.3
17
Data Analysis
8.8
283
9.3
18
8.6
269
9.2
18
Decision Making
8.9
275
9.2
18
8.0
251
8.4
17
7.9
254
8.3
17
8.2
226
8.9
18
Generative AI
7.2
6
Not enough data
6.9
6
Not enough data
Database
Not enough data
9.3
14
Not enough data
8.7
15
Not enough data
9.0
13
Integrations
Not enough data
8.0
9
Not enough data
8.0
9
Platform
Not enough data
8.8
14
Not enough data
9.5
14
Not enough data
8.0
9
Processing
Not enough data
7.7
11
Not enough data
9.2
12
Building Reports
Not enough data
9.2
22
Not enough data
9.2
21
Not enough data
7.6
13
Not enough data
8.3
18
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Altair AI Studio and TIMi are categorized as Data Science and Machine Learning Platforms, Analytics Platforms, and Predictive Analytics
Unique Categories
Altair AI Studio is categorized as Text Analysis and Generative AI Infrastructure
TIMi is categorized as Data Preparation, Big Data Processing and Distribution, and Statistical Analysis
Reviews
Reviewers' Company Size
Altair AI Studio
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
TIMi
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Higher Education
18.4%
Education Management
15.4%
Information Technology and Services
9.2%
Research
6.9%
Computer Software
6.9%
Other
43.2%
Information Technology and Services
12.5%
Financial Services
9.4%
Oil & Energy
7.8%
Banking
7.8%
Education Management
6.3%
Other
56.3%
Most Helpful Reviews
Altair AI Studio
Most Helpful Favorable Review
Verified User in Food & Beverages
Easy Data Connectivity to various databases. Crisp-DM support from start to end. TurboPrep and AutoModel for easier and faster models and results.
Most Helpful Critical Review
Verified User in Biotechnology
RapidMiner seemed to freeze at times, and was limited in terms of features and abilities. For example, extracting specific features out of a data set is limited compared to coding.
TIMi
Most Helpful Favorable Review
Verified User in Marketing and Advertising
regardless of the size of the machine you're using, TIMi/Anatella just delivers: - I've loaded about 1TB of compressed Json documents straight into the tool - the transformation to an actual matrix of features was by far the quickest I've used (vs R vs...
Most Helpful Critical Review
Matej K.
Verified User in Supermarkets
it is mainly for windows (great for most companies) the python (and R) connectors are great... however in very restrictive environments difficult to setup luckily the support is great: I had several updates based on my specific request in the tool adding...
Verified User in Food & Beverages
Easy Data Connectivity to various databases. Crisp-DM support from start to end. TurboPrep and AutoModel for easier and faster models and results.
Verified User in Marketing and Advertising
regardless of the size of the machine you're using, TIMi/Anatella just delivers: - I've loaded about 1TB of compressed Json documents straight into the tool - the transformation to an actual matrix of features was by far the quickest I've used (vs R vs...
Verified User in Biotechnology
RapidMiner seemed to freeze at times, and was limited in terms of features and abilities. For example, extracting specific features out of a data set is limited compared to coding.
Matej K.
Verified User in Supermarkets
it is mainly for windows (great for most companies) the python (and R) connectors are great... however in very restrictive environments difficult to setup luckily the support is great: I had several updates based on my specific request in the tool adding...
Discussions
To predict 8 test values using 12 other test values, you can use a machine learning model. First, organize your data into a suitable format, with the 12 test values as features and the 8 test values as targets. Split your data into training and testing sets. Train a regression model, such as linear regression, decision tree, or a more complex model like a neural network, on the training set. Evaluate the model's performance on the testing set to ensure it generalizes well.
To find a relation between parameters, perform exploratory data analysis. Use statistical methods like correlation analysis to identify relationships between variables. Visualize the data using scatter plots, heatmaps, or pair plots to observe patterns. Consider using dimensionality reduction techniques like PCA to understand the underlying structure of the data. Finally, validate your findings with domain knowledge or further statistical testing.
3 comments
NJ
Hello Daniel,
Yes, you are right setting each one of 8 as a function of those 12 and using simple regression does solve it. I tried previously in the same...Read more
How do I deploy a process successfully designed in Rapidminer in the field?
1 comment
II
first determine the data object that will be processed in rapidminer, the data used is not structured, and not derived from the questionnaire...Read more
What is the best tool for predictive analytics for Manufacturing Industries?
1 comment
FZ
RapidMiner has an initial workflow for predictive maintenance.
You could start experimenting fast and then fine-tune the model.Read more
the processes developed can be automated in the background minimizing the use of resources?
2 comments
LM
Yes. Definitely. You can launch it through command line, either in Windows or Linux (using Wine. Works perfectly fine)Read more
Do you think Timi should start exploring artificial intelligence?
1 comment
DS
Hola Carmen, thanks for the question! it really depends how you define AI: we have been pioneering AI since 2007 with the release of Timi Modeler, the very...Read more
What is TIMi Suite used for?
1 comment
DS
TIMi is used for 3 main purpose:
- simplify Data Intetration: with native connection to most data sources, our ETL tool makes it easy to join, aggregate,...Read more
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