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Compare Grafana Labs and IBM Cloud Pak for AIOps 
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At a Glance
Market Segments
Mid-Market (43.7% of reviews)
Enterprise (39.3% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Grafana Labs
Star Rating
(142)4.5 out of 5
Market Segments
Mid-Market (43.7% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Grafana LabsIBM Cloud Pak for AIOps
Star Rating
(63)4.2 out of 5
Market Segments
Enterprise (39.3% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for AIOpsSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Grafana Labs excels in Data Visualization with a score of 9.6, allowing for highly customizable dashboards that users find intuitive and visually appealing. In contrast, IBM Cloud Pak for AIOps has a lower score of 9.2 in this area, indicating that while it offers good visualization options, it may not be as flexible or user-friendly as Grafana.
- Reviewers mention that Grafana Labs provides superior Monitoring capabilities, particularly in Real-Time Monitoring with a score of 8.6, which is crucial for users needing immediate insights. IBM Cloud Pak for AIOps, while also strong, has a slightly lower score of 8.5, suggesting it may not be as responsive in real-time scenarios.
- G2 users highlight that Grafana Labs has a robust Alerting system with a score of 8.1, which is praised for its timely notifications and multi-mode alerts. Conversely, IBM Cloud Pak for AIOps scores 7.9 in this area, indicating that its alerting features may not be as comprehensive or effective as those offered by Grafana.
- Users on G2 report that IBM Cloud Pak for AIOps shines in Cloud Resource Management with a score of 7.7, providing tools that help manage cloud costs effectively. Grafana Labs does not focus on this area, which may be a disadvantage for users looking for integrated cloud management solutions.
- Reviewers mention that Grafana Labs has a strong focus on Performance Monitoring, scoring 8.5, which is essential for users needing to track application performance closely. IBM Cloud Pak for AIOps also scores 8.5, but users report that its performance features are more complex and may require a steeper learning curve.
- Users say that IBM Cloud Pak for AIOps offers better AI/ML Assistance with a score of 7.3, which is beneficial for organizations looking to leverage machine learning for operational insights. Grafana Labs, while strong in other areas, does not emphasize AI/ML features as much, which could be a drawback for users seeking advanced analytics capabilities.
Pricing
Entry-Level Pricing
Grafana Labs
No pricing availableIBM Cloud Pak for AIOps
No pricing availableFree Trial
Grafana Labs
Free Trial is available
IBM Cloud Pak for AIOps
No trial information availableRatings
Meets Requirements
8.8
108
8.8
32
Ease of Use
8.5
110
8.0
32
Ease of Setup
8.3
63
7.9
20
Ease of Admin
8.6
51
7.9
19
Quality of Support
8.0
86
8.4
31
Has the product been a good partner in doing business?
8.3
42
8.8
20
Product Direction (% positive)
8.8
106
7.3
26
Features by Category
Functionality
9.7
10
Not enough data
8.5
10
Not enough data
7.6
9
Not enough data
9.0
10
Not enough data
8.0
10
Not enough data
9.2
10
Not enough data
Agentic AI - Database Monitoring
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
Monitoring
9.0
17
Not enough data
8.8
16
Not enough data
8.8
17
Not enough data
9.0
18
Not enough data
Not enough data
Not enough data
Administration
8.8
16
Not enough data
7.7
16
Not enough data
7.8
16
Not enough data
Not enough data
Not enough data
Analysis
7.9
15
Not enough data
9.5
18
Not enough data
6.8
14
Not enough data
Agentic AI - Cloud Infrastructure Monitoring
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
AI Automation - Cloud Infrastructure Monitoring
Not enough data
Not enough data
Not enough data
Not enough data
Functionality
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
Not enough data
7.7
5
Not enough data
8.7
5
Agentic AI - Cloud Management Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Monitoring
8.9
9
Not enough data
9.3
9
Not enough data
8.5
9
Not enough data
8.0
5
Not enough data
Management Tools
8.3
9
Not enough data
7.6
9
Not enough data
8.1
9
Not enough data
Generative AI
8.0
5
Not enough data
8.0
5
Not enough data
Agentic AI - Incident Management
Not enough data
Not enough data
8.3
5
Not enough data
9.3
5
Not enough data
8.3
5
Not enough data
Not enough data
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
Visibility
9.5
17
Not enough data
8.2
17
Not enough data
8.2
17
Not enough data
Monitoring and Management
8.2
16
Not enough data
8.2
17
Not enough data
9.0
17
Not enough data
Agentic AI - Log Monitoring
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
Monitoring
8.6
16
Not enough data
8.6
16
Not enough data
8.8
17
Not enough data
7.4
15
Not enough data
8.1
15
Not enough data
Response
9.2
16
Not enough data
8.3
15
Not enough data
8.5
16
Not enough data
Agentic AI - Application Performance Monitoring (APM)
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
Performance
7.8
16
Not enough data
8.2
15
Not enough data
Functionality
7.9
15
Not enough data
7.9
14
Not enough data
7.8
13
Not enough data
8.5
13
Not enough data
Alerts management
8.9
23
Not enough data
8.8
26
Not enough data
9.1
27
Not enough data
Monitoring
8.5
26
Not enough data
8.8
27
Not enough data
8.4
25
Not enough data
8.6
24
Not enough data
Automation
8.6
22
Not enough data
8.8
24
Not enough data
Analysis
8.4
25
Not enough data
8.5
25
Not enough data
9.1
27
Not enough data
8.5
25
Not enough data
Issue Resolution
8.3
21
Not enough data
8.3
20
Not enough data
8.4
22
Not enough data
Generative AI
6.2
7
Not enough data
Agentic AI - IT Alerting
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
Telemetry Collection & Ingestion - Observability
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Observability Software
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
Visualization & Dashboards - Observability
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Correlation & Root Cause Analysis - Observability
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Scalability & Ecosystem Integration - Observability
Not enough data
Not enough data
Not enough data
Not enough data
AI Features - Observability
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - AWS Marketplace
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
Not enough data
Not enough data
Organization
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Development
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
Grafana Labs and IBM Cloud Pak for AIOps are categorized as Application Performance Monitoring (APM)
Unique Categories
Grafana Labs is categorized as AWS Marketplace, Container Monitoring, Incident Management, Log Monitoring, Cloud Infrastructure Monitoring, Database Monitoring, IT Alerting, and Observability Software
IBM Cloud Pak for AIOps is categorized as Other IT Management, Container Management, and Cloud Management Platforms
Reviews
Reviewers' Company Size
Grafana Labs
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Cloud Pak for AIOps
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
Information Technology and Services
24.4%
Computer Software
22.2%
Financial Services
5.9%
Telecommunications
4.4%
Internet
4.4%
Other
38.5%
Information Technology and Services
14.3%
Computer Software
14.3%
Telecommunications
10.7%
Management Consulting
8.9%
Banking
5.4%
Other
46.4%
Alternatives
Discussions
.
1 Comment
PC
Its help to Monitoring, analysis of our app and also provide graphic visualisation and alert Tigger system.Read more
Grafana Labs has no more discussions with answers
IBM Cloud Pak for AIOps has no discussions with answers
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