erwin Data Modeler Reviews

My main use case for erwin Data Modeler is to implement a single data architecture design department so everyone is using erwin Data Modeler for their data models to be a transactional application or a data repository. Everyone in the company and every project is using it for future implementations, modifications, new projects, enhancements, migrations, and everything.

I have more to add about my main use case and other recent projects where erwin Data Modeler played a key role, as it is a very good tool for data modeling and to control the different data models. At Nissan, there are several applications and different types of applications, and with erwin Data Modeler, the company is able to centralize and have a single language for data modeling and data architecture.

erwin Data Modeler's best feature that stands out for me is the Data Mart portal.

Before Mart Portal, we used to have a repository with shared folders, but now with Mart Portal, everyone is contributing and collaborating using erwin Data Modeler, so it is used as a development repository. This is one example of how erwin Data Modeler and Mart Portal are helping in daily work.

Another feature that stands out for me is the ability to compare data models, which is a good feature because you can compare data models between different database engines. It is also very useful to automate some tasks, such as the ability to import several columns or to translate from logical model to physical model.

erwin Data Modeler has positively impacted my organization by allowing us to implement the data architecture with the data strategy about six to eight years ago, since it allowed us to have a single language and implement new Nissan standards, naming conventions, constraints, and features. It also allowed us to reduce time and cost on generating data models and DDLs, as everything is centralized and everyone interested in accessing that in the organization can do so, allowing us to obtain information from data models and generate reports for some business areas.

Regarding improvements, the first thing I would mention is that every release has some issues, some of which are related to current functionalities, which means they often seem not very well tested or affected in the development process of the new version, leading to issues until that is released. Additionally, some important features such as importing from flat files took a lot of time or several releases to be addressed, and new functionalities for databases sometimes also take a long time. The tool is not too intuitive and you often have to keep searching until you find the option, so making the tool more intuitive is something that could be improved.

erwin Data Modeler needs to enhance the AI capabilities and integrate them with erwin Data Modeler functionalities, as more work is needed there.

The accuracy and reliability of output regarding erwin Data Modeler's AI capabilities also need enhancement, as it is a good start but not very useful in daily work, leading us to see more value in keeping the current erwin Data Modeler with the old options instead of using the new AI functionality.

I have been using erwin Data Modeler for six years.

While I do not have any exact amount, I can say it has helped to reduce the time that developers, designers, and even some domain data architects spent on their tasks by around thirty to fifty percent.

My advice for others looking into using erwin Data Modeler is to understand the functionality and their needs. When they start using erwin Data Modeler, they should find the value for their needs instead of just implementing it without prior knowledge. It is preferable to know the tool's capabilities and go from there. I have given this review a rating of eight out of ten.

erwin Data Modeler is primarily used for data modeling, including logical data modeling, physical data modeling, and conceptual data modeling.

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. All of this information can be captured in this tool.

It is beneficial for collaboration among business, IT, and data teams.

This tool is beneficial to any organization as it is foundational. There is no better way than this, and it is a must-have for every organization, whether large or small.

The solution can be improved. When you examine SQL DBM and compare its features, you can understand what improvements could be made.

I have been working with erwin Data Modeler for a long time, since 2009 and 2010.

I have never computed the ROI, but I can see that there is subjective ROI. Without any quantitative numbers, we can see the business benefits.

I do not know the price for the non-enterprise version for single desktop users.

erwin Data Modeler is a good product, but I recently experienced a problem where I was not able to open an erwin Data Modeler file because its version had automatically changed. I managed to recover the file by using the trial version of erwin Data Modeler version 15.

Currently, customers are using SQL DBM instead of erwin Data Modeler. I am working with a Helion customer who is trying to use SQL DBM. SQL DBM is a newly released cloud-based data modeling tool.

SQL DBM is another data modeling tool worth considering.

erwin Data Modeler is good for creating visual representations of data structures. You create a new project and models by building entities and defining the relationships among them.

I have never used erwin Data Modeler for data integration purposes, so I am not aware if such a feature exists.

erwin Data Modeler is about metadata, not just data. It is designed to maintain the enterprise-wide data model, including the structure of data and the relationships among those datasets. This is the information documented in the tool. When somebody wants to understand the data in an organization, they cannot navigate what data is maintained unless they have the logical data model or physical data model. To understand what data exists, someone has to examine those logical data models and physical data models.

In an organization, an enterprise version should always be used where multiple users can access it simultaneously.

I would rate this product a seven out of ten.

I use erwin Data Modeler as the modeler, utilizing the desktop version to develop and design tables, determining which attributes belong to which tables and designing their relationships. Another software developed by Quest, called erwin 360, is a public version that allows my leaders to view the models I created on a webpage, review my work, and give feedback. This is the main use case in our work.

In our case, we have 80 tables, each with potentially hundreds of attributes. Taking a simple screenshot wouldn’t be effective, as it wouldn’t be readable for others. However, erwin Data Modeler offers a very useful feature called diagram generation. This feature allows us to create a PDF file that clearly illustrates the details of each table, including its attributes and relationships. The representation in this PDF is quite effective, making it easy to share with others for reviewing the model.

erwin Data Modeler helps improve data governance frameworks. For instance, we can specify that each table must have only one unique attribute. If we accidentally duplicate attributes in a table, we'll identify the error immediately. Additionally, because Erwin serves as a source of truth, all other platforms and databases rely on it for their data deployment. This makes it much easier to manage data models. We won’t encounter issues like having to rename a column in Databricks and then rename it again in Snowflake, which can cause significant problems. Whenever we need to update the model, we can simply change it in the logical model. We can then create multiple physical models accordingly and deploy those physical models. I would say this approach is very helpful for data governance and maintaining control.

In terms of improvement in collaboration between business, IT, and data teams, we don’t have many teams involved in our work—just another data modeler like me and the leaders who are using erwin 360. So far, it’s working well. We are using merge functionality for version control, so there are no model version conflicts at all.

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. It is very easy, and because there is no comparison, every feature in erwin Data Modeler is very powerful and exactly meets our expectations. 

erwin Data Modeler could improve its UI as it still feels old school and not very modern. 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. Every time I need to find a feature, I have to contact the erwin support team. If there were detailed documentation of its features, that would be great. The UI can also improve, and I have faced issues where diagrams appear different in the Data Modeler versus erwin 360. If they could fix those bugs, that would be better.

In terms of integration, it’s more powerful than I initially expected. However, there are still some minor issues. For instance, when I generate DDL (Data Definition Language) for Databricks using a prebuilt template, everything works fine. The problem arises when I have a definition for a table or attribute that includes double quotes. Databricks does not accept this format, which prevents me from deploying the generated DDL. It would be beneficial if erwin Data Modeler could provide an error message indicating that using double quotes in definitions may lead to deployment issues. Additionally, if erwin Data Modeler could offer alternative solutions for handling double quotes in definitions, that would be very helpful. Overall, I am satisfied with the integration of erwin Data Modeler with ProView, Databricks, and Snowflake. I have used various tools, and so far, my experience has been positive.

I have been using erwin Data Modeler for almost one year and a half.

I do see some stability issues with erwin Data Modeler. Sometimes when I want to open the attribute editor, it stops working and the whole application freezes. I have found a solution online regarding the registry, but I have already noted that in a Word document on my laptop, so every time I face the same issue, I just follow that solution. If they could solve this issue, it would be easier for me next time.

Regarding scalability, erwin Data Modeler is performing well; from a few tables to 100 tables, it is working effectively so far.

I have contacted their technical support several times. The quality and speed of their support are excellent; everyone is very helpful, and they can solve problems quickly.

Positive

I have not used any alternatives to erwin Data Modeler or similar solutions as I did not find any alternatives.

When I first started with erwin Data Modeler, it was difficult. Starting erwin Data Modeler is very easy, but connecting it with the Mart portal was quite difficult, possibly due to our company's security settings and firewall settings. Overall, that process took me one to two months, so I would not say it was easy. It took me approximately one month to fully understand how to use erwin Data Modeler.

erwin Data Modeler requires some maintenance on our end. I recently contacted their technical support because some issues appeared unexpectedly. Luckily, we still have their maintenance coverage.

I do not recall the pricing from about a year and a half ago, but it seems reasonable.

erwin Data Modeler is effective in managing data across different environments, but we only work with SQL, SQL Server, and Snowflake; I did not interact with all environments, so it is only structured data. 

I would rate erwin Data Modeler an eight out of ten.

I have used Erwin for the last 20 to 30 years. As a data architect, I primarily use the data modelling tool. The MODEL MART functionality offers version control.

One of the best aspects of the tool is its reverse engineering capability. I can connect to a database and generate a new model. It creates foreign key relationships, both defined and implied, mapping them in my diagram. The ease of toggling from a logical model to a physical model is a great feature. It makes my job much easier to visualise my data model and relationships. Transitioning from a logical to a physical environment with just a switch is key. If I define my target database, it can generate my DDL for forward engineering.

As a documenting tool, it's solid, though its reporting could be more robust. The reporting mechanisms could be more intuitive regarding report creation. It can generate reports in CSV files, displayed like spreadsheets with a little Excel logo. However, it doesn't export directly to an Excel spreadsheet or Google Sheet. Adding this capability would be helpful. Currently, creating an Excel spreadsheet requires converting from CSV, which is inconvenient.

I have used Erwin since 1996.

As someone who has used it for a long time, I have seen stability vary from version to version. New versions often introduce enhanced features but may cause model crashes due to memory exhaustion. An example was several years ago when transitioning to 64-bit systems while still running a 32-bit application. This issue has been fixed, but earlier versions were less stable despite having many features.

It can support very large models but is resource-intensive. On a scale of one to ten, I would rate it probably a nine, making it a leader in data modelling. However, some tools can feel clunky, giving a Windows 98 vibe.

Now that they are with Quest, they are quick to handle issues. Quest is committed to keeping the product robust. I would rate them a nine out of ten. Nobody is perfect, however, they deserve a nine.

Positive

The initial setup is fairly easy. I need a license key provided by the company, placed in a specific directory. Upon startup, it looks for this license key, matching it with my workstation. There is a small hassle if you upgrade your computer, however, support is usually very good.

The difference between using a data modeling tool like this and walking into a shop without one is revolutionary. It replaces manual charting in Visio with a structured tool, providing significant return on investment.

I currently am investigating SQLDBM and DBSchema for an enterprise solution while testing HACKOLADE for an individual / local use.

I recommend it for those doing strictly data modelling. I can't give a recommendation for enterprise architecture as I haven't used it enough. My overall rating is eight out of ten.

I primarly use erwin Data Modeler for modeling purposes. Once we have the business requirement, we create the models in erwin Data Modeler, and then we perform forward engineering to get the query set and create the tables accordingly in SQL Server.

The best features of erwin Data Modeler include the forward engineering tool, which gives you the schema according to the data model that you generate. When working in legacy models such as data migration projects, the reverse engineering tool is beneficial because you can directly get the older models from the legacy system, including old data warehouses, then obtain the data models accordingly, make a few changes according to the business requirement, and create the new model.

The UI in erwin Data Modeler can be improved significantly because when any new person opens the tool, all the toolbars are kept open with many tools in view, making it appear chunky. If possible, suggestion models could be added. With AI tools available, whenever someone creates a data model, the tool could suggest better ideas to normalize the data models further based on knowledge and normalization principles.

I have been using erwin Data Modeler since 2021, though not continuously; I have used it on a few projects.

I rate the stability of erwin Data Modeler highly; it is a stable product.

I rate scalability at nine.

Overall, considering other feature scopes, I rate erwin Data Modeler at eight. My overall review rating for this product is nine.

For erwin Data Modeler, the use case was to create a data model for the organization. It articulates how data flows throughout the organization. For example, we have an employee table with two types of employees: permanent employees and contract-based employees. Contract-based employees are hired from an external organization. In the table structure, we would have multiple tables including employee, permanent, contract employee, and external organization. However, we did not want multiple tables. We wanted to combine them into one super table to reduce the normalized form. This approach is called a super-type rollup.

We did not use erwin Data Modeler for AI purposes. It was used for the migration part from SQL Server to the Azure Cloud. I did not work on the AI part for that project.

The project I was working on is based in the finance domain. For whatever quarter expenses our client had, we needed to communicate that with the client-side finance team management. That communication was not handled by me. I created the model and handed it over.

The best feature that I loved about erwin Data Modeler is the transformation part. We can create two types of models: the physical and logical models. Suppose there are multiple relationships such as one-to-one relationships, many-to-one relationships, and many-to-many relationships. If we want to reduce the size and optimize the data model, there is a transformation with an inbuilt functionality that helps resolve these issues. When one table is reflecting to ten other tables, it becomes very difficult to find relationships between them. If there are tens and hundreds of tables, finding relationships becomes increasingly complex. However, erwin Data Modeler has an inbuilt transformation that helps resolve many-to-many relationships and provides a better data model. This means I do not have to manually go through each and every table to find the relationships involved.

The tool is also very intuitive and easy to use. It is a simple drag-and-drop interface where we can create ER diagrams and import multiple projects. There is an Excel file where we write all the schemas and columns present in the table along with their data types. This Excel file has a VBA script. Once we finish putting all the data into that Excel file, we generate the model using that VBA. We then import that file into erwin Data Modeler and it is almost done. The transformations and other operations are the later part of the process.

As we all know, AI is taking up a majority of things. I felt that erwin Data Modeler is a bit of an outdated tool. It needs a new look and integrating AI into it would be much better for learning. AI would guide us on what operations we have to go through. If we are stuck somewhere, we could query the tool directly and ask about data modeling operations, and it would help us. Otherwise, we have to search on YouTube or Google or other sources to learn how to use erwin Data Modeler. An inbuilt guide within the tool would be much better, and an AI guiding tool would be even more helpful.

I have been working in my current field for three and a half years.

I have never faced any instability issues.

I did not have the opportunity to try other data modeling tools because my company had only one data modeling tool with just one erwin Data Modeler license.

I joined the company after erwin Data Modeler was already deployed. Whatever new data models came up, I had to make the data models and hand them over to my superiors.

I have no idea about the setup cost because I did not buy the license.

I would appreciate more information because I do not have much knowledge about PeerSpot. The team that contacted me on LinkedIn talked with me about erwin Data Modeler. I worked on it for four to five months. The last time I worked on it was last year in August. It is not difficult to learn how to use erwin Data Modeler. It is very easy, and there are reference materials available on YouTube. I did not face any difficulties learning the tool. The issue was not with erwin Data Modeler itself but with the organizational constraints. I did not have access to everything, which prevented me from exploring the tool further. I would give this review a rating of eight out of ten.

I am using the solution for data modeling. We also use erwin Data Intelligence Suite for data governance.

We like that we can go straight from Data Modeler to Data Intelligence Suite. We can go from the business glossary to the data catalog. It gives us a holistic view. The product lets us import different types of models from various databases. It also allows us to export or implement them within the same databases based on new changes.

The modeling capability is cumbersome. It doesn't allow us to put different types of objects in there. We can only put data objects. It doesn’t allow us to put any class structures and enterprise architecture objects. We can only do data monitoring. We can't do a holistic view. It's quite cumbersome to enter data. We cannot type things into a sheet. We always have to open the object and enter it.

The layout is a very old-style diagram. The product must allow users to put different types of objects and link them to data objects. The tool must provide large data objects under which there can be other data objects. For example, if a customer is a large data object, it must then contain the customer’s name, address, and type. The interface must be improved.

I have been using the solution for more than ten years. I am using the latest version of the solution.

I rate the tool’s stability a seven out of ten. It doesn’t stay up all the time. The stability must be improved.

I rate the tool’s scalability a seven out of ten. We have some issues with performance, but I'm not sure if it's us or the tool. We have 50 to 150 users.

The technical support team is quite helpful. The team members don't always know their stuff. Sometimes, we end up teaching them things, but they do try to be helpful.

Neutral

I have used Rational Rose, Visual Paradigm, and Oracle’s old product. I use Visual Paradigm for my personal use cases. I prefer Visual Paradigm. It has a lot of features that erwin doesn’t. The only problem with Visual Paradigm is that it has many license levels. I only have a cheap license. However, its capabilities are much stronger. It is a lot easier to use than erwin, and it produces much nicer diagrams.

The solution is cloud-based. We use both AWS and Azure as our cloud providers. Maintenance is done automatically by the vendor.

The tool is expensive. It is not worth the price. I rate the pricing a three out of ten.

We are looking for other tools to replace the solution. We're going to do an RFP for data modeling, data catalog, data quality, and marketplace. The vendor is trying to charge for Data Intelligence Suite like it is an enterprise tool, but it's still getting patched together. I have a hard time giving erwin a strong recommendation, but it's a tool that works and does what it says on the box. It could be made a little better. Overall, I rate the product a seven out of ten.

We are implementing erwin to streamline data modeling and automate network changes for increased efficiency and comprehensive data development. This option simplifies the need for better data indexing.

Quest can create conceptual and physical data models to facilitate effective communication between business and IT. It can also integrate expertise from various engineering and database systems within your organization to enhance data management and administration.

I have been using erwin Data Modeler by Quest for four years.

I rate the solution’s stability an eight out of ten.

We are testing the capacity in our environment for more than six thousand databases.

When we were working with third-party providers, they were giving very good support.

The initial setup depends on the tool if you are using the data model environment. Stopping the server could be complex and require strong expertise.

If you have everything set up and configured, Erwin is straightforward. You can deploy it in a few hours. In our case, it took a couple of months to address internal conditions, assign machines, and set up everything for the services.

I rate the initial setup a six out of ten, where one is difficult and ten is easy.

The reseller set up the whole department.

The product is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.

Reverse engineering is a very powerful feature. I have used it many times when working with clients, which has helped solve implementation issues.

Erwin utilizes artificial intelligence to automatically create definitions and generate logical or physical data models tailored to specific industries.

I recommend the solution.

Overall, I rate the solution a ten out of ten.

We use the solution for data modeling.

We believe that the solution would help provide some structure to our data modeling and data design practices.

The product allows us to reuse entities and attributes. Whether we're working on a conceptual or logical model, once we have defined them, we can reuse them rather than defining them all over again. It's a clever feature and helps with our work.

We can only get licenses through partners. We cannot purchase directly from Quest. The partners end up charging a big margin on top of the actual price even though they are not providing any service. It was a letdown.

I have been using the solution for four months.

I rate the tool’s stability an eight out of ten. The tool has crashed a couple of times. The stability must be improved.

I am the only person using the tool in my organization. We plan to increase the usage, but it is currently not being used much.

The support personnel are a bit slow in responding. The vendor talks about providing 24/7 support, but it could take 24 to 36 hours to get a response. The communication is just via email. It slows down the whole troubleshooting process.

Neutral

The initial setup was easy. I rate the ease of setup a ten out of ten. It took me five minutes to deploy the product. To deploy it, I downloaded the software, ran the executable, and it installed itself. I did the deployment myself.

The solution is expensive. I rate the pricing a nine out of ten. The price is not fixed. The product does not have a clear pricing model.

We evaluated ER/Studio but did not like its pricing structure. They have different versions which require multiple licenses for the applications we use. It was not easy to use. We preferred the pricing model of erwin Data Modeler.

The amount of data the tool works with is minimal, so scalability is irrelevant to the tool. It just uses metadata. People looking to use the solution must compare it with other tools like ER/Studio. ER/Studio and erwin Data Modeler are quite similar in the functionality they offer. It all comes down to what works for us in terms of pricing. Overall, I rate the solution an eight out of ten.

I use the solution for reverse engineering as well as forward engineering. I do logical and physical modeling, and some of what I'm doing right now is reverse engineering from actual databases because they have no diagrams. The solution helps me diagram the current and help me design the future.

Forward engineering, DDL generation, reverse engineering, and reporting are the most valuable features of the solution.

The solution's model mark could be better because it crashes sometimes.

I have been using erwin Data Modeler by Quest for many years.

erwin Data Modeler by Quest is a stable solution.

I rate erwin Data Modeler by Quest a nine out of ten for stability.

To add users, you have to start using the model mark, which is not great. I rate erwin Data Modeler by Quest a seven out of ten for scalability.

The solution’s technical support is good.

Positive

I have previously used IDERA ER.

The solution’s initial setup is easy.

I have seen a return on investment with the solution because I can't do my work for my company without it.

erwin Data Modeler by Quest is an expensive solution.

Before choosing erwin Data Modeler by Quest, I evaluated PowerDesigner. I chose erwin Data Modeler by Quest because it has the most features I might need in the future, and the report writing is really good.

I am using the latest version of erwin Data Modeler by Quest. I recently built a data model for integration with another software product that we're going to purchase. I did it really fast with erwin Data Modeler by Quest. If I didn't have the solution, I couldn't have done that, and I couldn't have shared the results.

I would recommend the solution to other users.

Overall, I rate erwin Data Modeler by Quest ten out of ten.