Erwin Data Modeler and Collibra Platform are major players in data management, with Erwin leading in data modeling and Collibra excelling in data governance. Erwin appears to have the upper hand in modeling efficiency, while Collibra leads in data governance and customization.
Features: Erwin Data Modeler offers robust visual data environments, complex transformation automation, and data integration that enhance user understanding. It also provides excellent visualization for collaboration and synchronization capabilities to keep data models up to date. Collibra Platform features strong data governance capabilities, extensive cataloging, metadata management, and customizable workflows that ensure data consistency and quality.
Room for Improvement: Erwin could improve its reporting capabilities, integration with data intelligence, and user-friendliness, especially in navigation and native interface operations. Users of Collibra suggest enhancements in connectivity with various data sources, a more intuitive interface, and reduced complexity and cost for smaller organizations.
Ease of Deployment and Customer Service: Erwin focuses on on-premises deployment with satisfactory support, though users desire better response times and legacy database integration support. Collibra is flexible with on-premises, cloud, and hybrid deployments, offering responsive support despite challenges in setup due to complex configurations.
Pricing and ROI: Erwin is considered expensive but justifiable due to its feature set that saves development time and provides consistency, with appreciated yet costly licensing options. Collibra is similarly viewed as a premium product, offering high value through operational efficiency and compliance but posing budget challenges for smaller companies.
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.
If three engineers save ten hours each per month using erwin Data Modeler versus manual modeling, that equals three hundred sixty hours saved per year.
It replaces manual charting in Visio with a structured tool, providing significant return on investment.
If the modeling is compromised, then the entire structure will be compromised.
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.
The quality and speed of their support are excellent; everyone is very helpful, and they can solve problems quickly.
This rating reflects my ability to effectively utilize the tool and get support for licensing issues, installation errors, or corrupted repositories end-to-end.
Quest is committed to keeping the product robust.
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 would rate it probably a nine, making it a leader in data modeling.
erwin Data Modeler had a very good standardization infrastructure and supported a controlled multi-user environment with check-ins and check-outs.
Performance can degrade during larger collaborations and requires tuning for optimal performance.
I rate the stability of Collibra Lineage as seven.
This lack of an auto-save methodology can be improved so that if a system crash occurs, work can be saved and rework can be avoided.
New versions often introduce enhanced features but may cause model crashes due to memory exhaustion.
Sometimes when I want to open the attribute editor, it stops working and the whole application freezes.
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.
The previous version of erwin Data Modeler used to crash unaccountably, but this one hasn't ever crashed on me, so it's been a lot more stable than the previous version that we had.
There are many features, and I would expect good documentation detailing each feature, including when and how to use it, to be very useful because data modeling is not very popular in the data area and there aren't many educational videos regarding erwin Data Modeler.
Erwin Data Modeler could improve in areas such as the interface, as there are features like copy and paste, creating duplicates, and the visualization elements and toolbars which feel quite old.
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.
For a cloud or SaaS standard edition, it typically runs around two hundred to two hundred ninety-nine US dollars per month.
It is more targeted toward an enterprise level since organizations looking to store business information and relationship values may consider the pricing.
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.
One of the key aspects of data governance is defining the data dictionary and clearly identifying which data is accessible by whom and what is not accessible, particularly regarding PII-related data.
The way the data is organized and you have a visual of that organization helps a great deal in terms of trying to remember what you did and trying to retrieve the information.
Migrating DDLs using erwin Data Modeler is easy because I just connect to the database and generate the data model from what is already implemented, making the process straightforward.
| Product | Mindshare (%) |
|---|---|
| Collibra Platform | 8.6% |
| erwin Data Modeler | 0.3% |
| Other | 91.1% |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 9 |
| Large Enterprise | 55 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 3 |
| Large Enterprise | 35 |
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.
Erwin Data Modeler provides an effective approach to visualizing and managing data models. It assists in creating, reversing, and synchronizing data models with ease, supporting logical and physical transitions while enhancing understanding across teams.
Erwin Data Modeler is a comprehensive tool designed for professional database management. It offers capabilities to organize and enforce standards, automating script generation with robust reverse engineering and DDL output. Users can manage complex data environments, capitalize on integration with data intelligence, and maintain large-scale databases smoothly. Despite its strengths, improvements in multi-language support, database integration, and reporting features are needed. Users benefit from extensive support for conceptual, logical, and physical database modeling, enhancing architectural design and data governance for platforms like SQL Server, Oracle, and Teradata.
What are the key features of Erwin Data Modeler?Erwin Data Modeler finds application in industries focused on robust data management, implementing it for enterprise data warehouses, business domain models, and operational systems. It supports architectural design and governance, aligning with business applications demanding precise data representation and visualization.
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