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Compare IBM Databand and Pantomath 
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At a Glance
Market Segments
Mid-Market (39.4% of reviews)
Enterprise (73.3% of reviews)
Entry-Level Pricing
Contact Us 1 GB / Month of Metadata Logged Per Year
Contact Us
IBM Databand
Star Rating
(67)4.4 out of 5
Market Segments
Mid-Market (39.4% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us 1 GB / Month of Metadata Logged Per Year
Browse all 2 pricing plansPantomath
Star Rating
(15)4.7 out of 5
Market Segments
Enterprise (73.3% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about PantomathSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that IBM Databand excels in "End to End visibility" with a score of 8.9, while Pantomath shines in "Data lineage" with a higher score of 9.5, indicating that Pantomath provides a more comprehensive view of data flow and transformations.
- Reviewers mention that IBM Databand has strong "Data Quality and Cleansing" capabilities, scoring 9.0, which is crucial for maintaining data integrity, whereas Pantomath's score of 7.3 in "Data quality monitoring" suggests it may not be as robust in this area.
- G2 users highlight that IBM Databand's "Quality of Support" is rated at 8.9, reflecting a strong customer service experience, while Pantomath outperforms in "Has the product been a good partner in doing business?" with a perfect score of 10.0, indicating exceptional partnership satisfaction.
- Users on G2 report that both products have similar scores in "Ease of Use" at 8.6, but IBM Databand's "Ease of Setup" at 8.3 is notably higher than Pantomath's 6.9, suggesting that IBM Databand may be easier to implement for new users.
- Reviewers mention that Pantomath's "Single pane view" feature scores 9.2, which is higher than IBM Databand's score of 8.3, indicating that Pantomath may offer a more streamlined interface for monitoring data.
- Users say that IBM Databand's "Automation" capabilities score 8.2, while Pantomath's score of 8.5 suggests it may provide slightly better automated workflows, which can enhance efficiency in data management tasks.
Pricing
Entry-Level Pricing
IBM Databand
Growth
Contact Us
1 GB / Month of Metadata Logged Per Year
- Monitored Pipelines | < 100
- Metadata Logged | Up to 500MB / month
- Alerting | Email. Slack. Pagerduty. Opsgenie
Pantomath
Pantomath
Contact Us
Our Data Observability Platform provides comprehensive, end-to-end visibility into your data pipelines, empowering teams to monitor, troubleshoot, and ensure the reliability of their data systems. With robust pipeline traceability, you can easily track data flow across systems, identify issues, and resolve them efficiently. Our platform also ensures data accuracy and completeness, supporting critical decision-making through reliable data. Automated data quality monitoring detects anomalies and issues in real time, ensuring your data consistently meets the highest standards.
Pipeline Traceability: Helps users track the flow of data across various systems, ensuring they can identify, trace, and resolve any issues in data pipelines.
Data Reliability: Ensures data is accurate, complete, and reliable, supporting key decision-making processes.
Data Quality Monitoring: Automated monitoring of data quality with alerts on potential anomalies or issues, ensuring data meets defined standards.
- End-to-End Monitoring
- Anomaly Detection
- Root Cause Analysis
Free Trial
IBM Databand
Free Trial is available
Pantomath
No trial information availableRatings
Meets Requirements
8.6
60
8.9
12
Ease of Use
8.6
62
8.2
15
Ease of Setup
8.3
31
6.9
15
Ease of Admin
8.0
23
8.3
10
Quality of Support
8.9
58
9.2
12
Has the product been a good partner in doing business?
8.3
23
10.0
10
Product Direction (% positive)
9.4
58
9.0
12
Features by Category
Data Source Access
8.6
27
Not enough data
8.6
29
Not enough data
8.8
28
Not enough data
Data Interaction
8.3
27
Not enough data
8.5
29
Not enough data
8.4
29
Not enough data
8.8
28
Not enough data
8.7
28
Not enough data
9.0
29
Not enough data
8.6
28
Not enough data
8.6
29
Not enough data
Data Exporting
8.5
27
Not enough data
8.2
28
Not enough data
8.8
29
Not enough data
Generative AI
8.5
8
Not enough data
Functionality
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
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
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - DataOps 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
Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Monitoring and Management
Not enough data
Not enough data
Not enough data
Not enough data
Cloud 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
Functionality
8.6
46
8.3
11
8.6
45
7.3
11
8.2
45
8.5
11
8.9
46
9.7
11
Management
8.3
45
8.5
11
8.3
42
9.2
11
8.5
44
8.6
11
8.7
42
9.5
11
8.6
44
8.6
11
Generative AI
7.3
11
6.4
6
Agentic AI - Data Observability
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
Functionality
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
Management
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
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
IBM Databand and Pantomath are categorized as Data Observability
Reviews
Reviewers' Company Size
IBM Databand
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Pantomath
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
22.7%
Computer Software
19.7%
Retail
9.1%
Computer & Network Security
7.6%
Financial Services
6.1%
Other
34.8%
Financial Services
40.0%
Logistics and Supply Chain
20.0%
Banking
13.3%
Information Technology and Services
6.7%
Human Resources
6.7%
Other
13.3%
Discussions
IBM Databand has no discussions with answers
Pantomath has no discussions with answers
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