

Camunda and erwin Data Modeler compete in process automation and data modeling respectively. Camunda appears to have an edge due to its flexibility and strong community support, whereas erwin Data Modeler excels in data visualization and consistency.
Features: Camunda is highly flexible with its open-source model and supports microservices and BPMN compliance, making it easy to use without extensive programming skills. It is valued for customizable integrations and a strong community presence. Erwin Data Modeler shines in visualization, reverse engineering, and maintaining data model consistency, which facilitates complex data management and collaboration for large data environments.
Room for Improvement: Camunda users see opportunities for enhanced UI customization, documentation, and API compatibility. Desired features include a built-in form builder and scalability improvements. Erwin Data Modeler needs enhancements in Complete Compare functionality, better support for big data platforms, and more intuitive navigation with a modern interface.
Ease of Deployment and Customer Service: Camunda supports versatile deployment options including private, public, and hybrid clouds. It benefits enterprise users with strong community-driven support but needs better documentation. Erwin Data Modeler supports primarily on-premises deployment, praised for its responsive technical support, though streamlined procedures and enhanced service offerings are anticipated.
Pricing and ROI: Camunda is cost-effective due to its open-source version, appealing to startups, although its enterprise version can be costly. Users appreciate its features for ROI in process efficiency. Erwin Data Modeler is perceived as pricey, posing a barrier for smaller organizations, but its feature set offers substantial returns for enterprises by ensuring data accuracy and streamlining management.
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.
AWS provides the best support, followed by Microsoft, and then Google.
They really understand deeply and in detailed fashion the solution.
They provide better support for the enterprise edition.
The quality and speed of their support are excellent; everyone is very helpful, and they can solve problems quickly.
Quest is committed to keeping the product robust.
Erwin Data Modeler requirements function at a standard level.
Camunda offers a high level of scalability, especially when using its SaaS model, which manages and scales implementations automatically.
ECS and Fargate make horizontal scalability very easy.
They have that REST layer, REST APIs layer that makes it easy to integrate and make it part of a microservices ecosystem and APIs.
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.
Regarding scalability, erwin Data Modeler is performing well; from a few tables to 100 tables, it is working effectively so far.
There haven't been any significant outages in my experience with Camunda.
We were not really concerned about the performance on the process itself because it was super simple, super straightforward, and it did not present itself as a bottleneck, nor did we feel it was adding additional time in the execution.
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.
More open documentation would be beneficial to understand the deployment process better and facilitate easier setup.
There is an issue where, in some situations, I need to scale up by observing both CPU and memory usage of containers, yet under the current options available at Amazon, this is not possible.
Since they made the move to cloud deployment in a more SaaS-oriented way, they do not invest too much in the community version.
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.
AWS pricing is very competitive compared to Azure and cheap compared to Google.
There is a licensing cost for using the SaaS model and Enterprise edition of Camunda.
It is more targeted toward an enterprise level since organizations looking to store business information and relationship values may consider the pricing.
EC2 makes scaling horizontally incredibly easy, especially when working under the ECS service.
Camunda's support for BPMN 2.0 is a great advantage because it allows us to have a common language to discuss technology and business in the same perspective.
The biggest difference between Camunda and Bonita might be that Camunda is simpler and more flexible for setting.
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.
One of the best aspects of the tool is its reverse engineering capability.
| Product | Market Share (%) |
|---|---|
| Camunda | 9.3% |
| erwin Data Modeler | 2.5% |
| Other | 88.2% |

| Company Size | Count |
|---|---|
| Small Business | 43 |
| Midsize Enterprise | 15 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 3 |
| Large Enterprise | 34 |
Camunda revolutionizes process orchestration by enabling seamless automation and integration with AI, human tasks, and existing systems while ensuring security and governance.
Built for collaboration between business and IT, Camunda empowers organizations to manage complexity, boost efficiency, and maintain competitive advantage. With a clientele of over 700 top organizations like Atlassian, ING, and Vodafone, Camunda is a trusted partner in designing, orchestrating, automating, and refining critical business processes to accelerate digital transformation. Its open-source nature, ease of use, and REST API integration make it a versatile choice for various needs.
What are Camunda's key features?
What benefits or ROI should users look for?
In banking, Camunda automates processes and manages transactions, while in telecommunications, it optimizes service orders. Governmental and public sectors benefit from workflow automation. Organizations often use either the enterprise edition or the open-source version to create APIs and manage business rules effectively.
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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