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.
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.
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 (%) |
---|---|
erwin Data Modeler | 0.0% |
erwin Data Intelligence | 1.8% |
Other | 98.2% |
Company Size | Count |
---|---|
Small Business | 1 |
Midsize Enterprise | 4 |
Large Enterprise | 14 |
Company Size | Count |
---|---|
Small Business | 14 |
Midsize Enterprise | 3 |
Large Enterprise | 29 |
Erwin Data Intelligence drives automation, supports data catalog and literacy, and offers Smart Data Connectors for efficient metadata handling. Its customization flexibility and integration facilitate enhanced data governance, visualization, analysis, and compliance.
Erwin Data Intelligence offers automation scripts that accelerate development, integrated data cataloging, data profiling, and lineage analysis to streamline information management. Users appreciate its capability in metadata harvesting, code engineering, and infrastructure integration. The tool provides flexibility to enhance governance and data visualization. While it performs well, users have noted challenges with API robustness and interface complexity, and there are opportunities to improve workflow integration, AI features, and large dataset handling. Companies rely on it for metadata management, automation of metadata mappings, and data governance to support compliance and literacy.
What are the main features of Erwin Data Intelligence?In industries such as finance, healthcare, and retail, organizations implement Erwin Data Intelligence for efficient metadata management and governance. It assists in automating lineage and mapping, supporting ETL procedures while enhancing compliance and data literacy efforts. Its flexibility and integration support create valuable data insights and governance improvements.
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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