Ping Identity Platform and Collibra Platform offer solutions for digital identity management and data governance, respectively. While both platforms excel in their areas, Collibra's comprehensive feature set makes it particularly attractive to enterprises seeking robust data governance.
Features: Ping Identity Platform provides strong identity management, authentication, and access control, integrating seamlessly with high security. It supports multifactor authentication, customizable policies, and offers extensive security integrations. Collibra Platform excels in data governance with features like data cataloging, privacy management, and AI-driven data lineage, providing users detailed insights and metadata management. Both platforms have powerful tools tailored to their core functionalities.
Room for Improvement: Ping Identity could enhance user interface and provide more flexible customization options to better meet diverse client needs. Additionally, expanding support for mobile devices beyond the current authentication methods may improve user experience. Collibra may benefit from simplifying integration processes with other tools and reducing the complexity of its configuration options to streamline setup and management. Another area of improvement is enhancing the user interface for greater ease of use by non-technical users.
Ease of Deployment and Customer Service: Ping Identity Platform is easier to deploy within existing infrastructures, offering robust integration support. Its clear documentation facilitates smoother deployment. Collibra provides a flexible cloud-based deployment that supports quick implementation and strong customer support with training resources, ensuring effective usage of its extensive features.
Pricing and ROI: Ping Identity Platform offers competitive pricing that delivers a high return on investment by mitigating security risks and streamlining access management. Collibra's pricing may be on the higher end, justified by its feature-rich offering, providing ROI through improved governance and compliance. Both platforms present cost-effective solutions, with the choice hinging on whether identity management or data governance is prioritized.
When considering the time and effort required to build a catalog and utilize it effectively, combined with the prices, it often does not make financial sense.
Implementing Collibra Data Catalog can be cost-effective if its features align well with the business requirements.
While there are no direct cost reductions, there is significant indirect cost reduction.
When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved.
The technical support from Collibra Governance is excellent.
I encountered some issues with data quality initially in Collibra Data Intelligence Platform, and they resolved those issues.
I have reached out to technical support for troubleshooting SAML certificate mismatches and federated errors between Ping and enterprise apps.
We were a big bank and had thousands of assets without any issues.
Collibra Lineage's performance is reliable, as the lineage harvest runs on the lineage server which operates on Collibra cloud.
I would rate the scalability of Collibra Lineage as a nine; it is a scalable solution for my business.
I rate the stability of Collibra Lineage as seven.
Users often find it challenging to utilize data governance tools, with ease of use ranked as an important criterion by 2028 standards.
There should be a reduction in cost as compared to other tools.
There is an issue with Collibra Catalog's pricing model, especially for organizations with many databases, as the initial package comes with a limited number of connectors.
I would like to enable ServiceNow Generative AI for auto-diagnosing PingFederate SSO failures and suggest remediation steps.
Ping Identity Platform has multiple products for access management, identity management, a solution for API security, a solution for authorization, and a product for identity verification.
Collibra has high initial costs for licensing that can be a barrier to small and medium-sized companies starting with it.
There are plans to increase license rates.
Adding modules like Privacy could become expensive.
My experience with Collibra's collaboration tools in improving data literacy has been quite good. I think it is one of the best for helping people understand and discuss certain data sets and manage workflows.
We have saved up to 30% of manual work as a specific process or workflow became faster.
The data lineage feature is beneficial for understanding where data is coming from.
The platform enhances security measures by analyzing multi-factor authentication attempts, highlighting suspicious patterns, and generating compliance reports.
It's a converged platform which can do both identity management, access management, and recently they are bringing privilege management capability as well.
| Product | Mindshare (%) |
|---|---|
| Collibra Platform | 8.6% |
| Ping Identity Platform | 0.7% |
| Other | 90.7% |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 9 |
| Large Enterprise | 55 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 2 |
| Large Enterprise | 20 |
Collibra Platform is preferred for workflows, data lineage, and a user-friendly interface. It enhances metadata management with robust collaboration, flexible customization, and powerful reporting, aiding organizations in effective data management.
Collibra Platform provides dependable solutions for metadata management, data lineage, and governance. It strengthens data governance with cataloging, glossaries, automation, and integration, supporting compliance and data quality management. Despite challenges with integration and metadata ingestion, the platform is vital for data governance programs, offering comprehensive AI capabilities and streamlined processes for enterprise data management.
What are Collibra Platform's key features?In industries, Collibra Platform supports IT teams through metadata management and data quality assurance. It is widely used for compliance initiatives like GDPR, speeding up digital transformation and enforcing policy management. Organizations employ it to consolidate business and technical metadata, ensuring effective enterprise-scale data management in diverse sectors.
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