Find out in this report how the two Data Governance solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
It replaces manual charting in Visio with a structured tool, providing significant return on investment.
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.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
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.
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.
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.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
From my experience, SAS Data Management is an expensive tool.
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.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
| Product | Market Share (%) |
|---|---|
| erwin Data Modeler | 0.0% |
| SAS Data Management | 1.0% |
| Other | 99.0% |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 3 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
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.
Every decision, every business move, every successful customer interaction - they all come down to high-quality, well-integrated data. If you don't have it, you don't win. SAS Data Management is an industry-leading solution built on a data quality platform that helps you improve, integrate and govern your data.
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