Camunda and Erwin Data Modeler are leading tools in the business process management and data modeling categories, respectively. Camunda has the upper hand in flexibility and open-source options, while Erwin excels in detailed data visualization and integration with database systems.
Features: Camunda's lightweight architecture and scalable support highlight its wide coverage of BPMN, CMMN, and DMN standards. It offers powerful modeling tools, a REST API for easy integration, and open customization without programming expertise. Erwin Data Modeler provides robust database visualization with reverse engineering, facilitating logical, conceptual, and physical database modeling. It ensures synchronicity between data models and sources and integrates business logic effectively.
Room for Improvement: Camunda's interface could use enhancements and better integration with diverse tech stacks. UI customizations often need external solutions. Erwin's UI feels outdated and cumbersome, necessitating simplification to meet modern design requirements. Reporting improvements and increased compatibility with big data platforms are also needed. Both platforms could expand documentation and support for better user onboarding and adaptability.
Ease of Deployment and Customer Service: Camunda is highly adaptable across public, private, and hybrid cloud environments, contrasting with Erwin's on-premises focus. While Camunda benefits from community support, its enterprise support needs clearer structures. Erwin is noted for good technical support, crucial for its complex setup, though real-time engagement improvements could enhance user satisfaction.
Pricing and ROI: Camunda stands out with its open-source model, offering a cost-effective entry point with options to upgrade to premium services. The enterprise version might escalate in cost, but the open-source version suffices for smaller tasks. Erwin's pricing is often seen as high but is justified by its comprehensive capabilities and benefits of concurrent licenses for larger teams. Camunda offers quicker ROI through workflow efficiencies, whereas Erwin's value is in its in-depth modeling for complex database management.
It replaces manual charting in Visio with a structured tool, providing significant return on investment.
AWS provides the best support, followed by Microsoft, and then Google.
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.
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.
I would rate it probably a nine, making it a leader in data modeling.
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.
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.
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.
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.
EC2 makes scaling horizontally incredibly easy, especially when working under the ECS service.
The biggest difference between Camunda and Bonita might be that Camunda is simpler and more flexible for setting.
Currently in the market, there is no competitor to erwin Data Modeler; everything is very powerful, such as performing reverse engineering from an existing database and deploying that on Databricks or Snowflake.
Transitioning from a logical to a physical environment with just a switch is key.
| Product | Market Share (%) |
|---|---|
| Camunda | 11.3% |
| erwin Data Modeler | 2.0% |
| Other | 86.7% |
| Company Size | Count |
|---|---|
| Small Business | 41 |
| Midsize Enterprise | 15 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 3 |
| Large Enterprise | 29 |
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?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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