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Compare IBM Decision Optimization and TIMi 
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At a Glance
Market Segments
Enterprise (60.0% of reviews)
Small-Business (36.9% of reviews)
Entry-Level Pricing
Free
Free
IBM Decision Optimization
Star Rating
(41)4.5 out of 5
Market Segments
Enterprise (60.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
Free
Browse all 2 pricing plansTIMi
Star Rating
(71)4.9 out of 5
Market Segments
Small-Business (36.9% of reviews)
Pros & Cons
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 TIMi Suite excels in Data Preparation with a score of 9.6, highlighting its robust Connectors feature that allows seamless integration with various data sources, while IBM Decision Optimization falls short with a score of 7.2 in Data Ingestion & Wrangling.
- Reviewers mention that TIMi Suite's Model Training capabilities are superior, scoring 9.5, which users attribute to its efficient handling of Pre-Built Algorithms. In contrast, IBM Decision Optimization's score of 7.4 indicates a less favorable experience in this area.
- G2 users highlight TIMi Suite's Quality of Support with a score of 9.3, noting that the support team is responsive and helpful. Conversely, IBM Decision Optimization's score of 8.6 suggests that while support is adequate, it may not meet the same level of user satisfaction.
- Users on G2 report that TIMi Suite's Ease of Use is a significant advantage, scoring 9.1, with many praising its intuitive interface and Drag and Drop functionality. IBM Decision Optimization, with a score of 8.7, is seen as slightly more complex to navigate.
- Reviewers say that TIMi Suite's Data Quality and Cleansing features are highly effective, scoring 9.5, which users attribute to its comprehensive tools for ensuring data integrity. In contrast, IBM Decision Optimization's performance in this area is less impressive, with a score of 8.9.
- Users report that TIMi Suite's Scalability is a strong point, achieving a score of 9.5, making it suitable for growing businesses. IBM Decision Optimization, however, has a lower score of 7.6, indicating potential limitations for users with expanding needs.
Pricing
Entry-Level Pricing
IBM Decision Optimization
IBM ILOG CPLEX Optimization Studio Free edition
Free
Explore and learn optimization and constraint programming modeling with our free edition. Try free edition:
https://www.ibm.com/account/reg/signup?formid=urx-20028
- Limited to 1000 variables and 1000 constraints, but models can be edited
- Use both the OPL/IDE and API modeling/solving
TIMi
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
IBM Decision Optimization
Free Trial is available
TIMi
Free Trial is available
Ratings
Meets Requirements
8.4
30
9.4
54
Ease of Use
8.7
30
9.0
52
Ease of Setup
8.3
14
9.1
23
Ease of Admin
8.7
14
8.5
19
Quality of Support
8.6
30
9.3
52
Has the product been a good partner in doing business?
9.2
14
9.3
20
Product Direction (% positive)
8.0
29
9.5
46
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
9.1
23
Not enough data
9.1
22
Not enough data
7.6
14
Not enough data
8.4
19
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
7.2
9
9.0
12
Model Development
7.9
7
8.6
12
8.3
7
9.1
13
8.3
7
9.2
13
7.4
7
9.5
14
Model Development
7.4
9
8.9
12
Machine/Deep Learning Services
7.9
7
Feature Not Available
7.4
7
8.7
10
6.9
7
Feature Not Available
6.9
7
9.1
9
Machine/Deep Learning Services
7.3
8
9.0
7
7.5
8
9.3
7
Deployment
8.3
7
8.8
10
8.1
7
8.9
11
7.6
7
9.5
14
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
Integration
Not enough data
Not enough data
Not enough data
Not enough data
Business Logic
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Decision Management 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
Statistical Tool
Not enough data
9.1
17
Not enough data
9.3
18
Not enough data
9.4
18
Data Analysis
Not enough data
9.3
19
Not enough data
9.2
19
Decision Making
Not enough data
9.0
19
Not enough data
8.4
18
Not enough data
8.4
18
Not enough data
8.9
19
Generative AI
Not enough data
Not enough data
Not enough data
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
9.1
23
Not enough data
9.1
22
Not enough data
7.6
14
Not enough data
8.4
19
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
IBM Decision Optimization and TIMi are categorized as Data Science and Machine Learning Platforms
Unique Categories
IBM Decision Optimization is categorized as Decision Management Platforms
TIMi is categorized as Data Preparation, Analytics Platforms, Predictive Analytics, Big Data Processing and Distribution, and Statistical Analysis
Reviews
Reviewers' Company Size
IBM Decision Optimization
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
Financial Services
14.3%
Education Management
11.4%
Computer Software
11.4%
Transportation/Trucking/Railroad
5.7%
Research
5.7%
Other
51.4%
Information Technology and Services
12.3%
Financial Services
9.2%
Oil & Energy
7.7%
Banking
7.7%
Education Management
6.2%
Other
56.9%
Discussions
IBM Decision Optimization has no discussions with answers
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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