erwin Data Modeler Reviews

My main use case for erwin Data Modeler is to design data models for the healthcare and retail industries.

I used erwin Data Modeler in my healthcare projects at my previous company, Innovaccer, where I designed data models for value-based care and a centralized data model for value-based care to manage healthcare patient data and ACO data.

Data modeling is the primary area where I have used erwin Data Modeler. I also use erwin Data Modeler in other areas such as maintaining lineage and several other use cases.

Having erwin Data Modeler, we stored data modeling in a particular erwin Data Modeler mart, and people from other teams who want to understand the data benefit from collaborative efforts, which increases productivity and enhances understanding of data.

In terms of outcomes, we have a number of data modeling licenses, and when we design data models, erwin helps people wanting to understand the data about the data model or what it represents. It also showcases data models in a nice pictorial way in PDFs or HTML formats, and even CSV, so we can generate customized reports that are helpful for other teams to understand the data model.

The best features erwin Data Modeler offers include the flow from CDM to LDM to PDM, the forward engineering feature which is very useful for capturing DDLs, and the bulk edit feature that is very useful when I want to edit multiple fields at once.

Regarding the forward engineering feature, generating a DDL of a particular schema after creating the PDM, or physical data model, helps me obtain the DDL and then use it for deploying the same schema into a target database. The bulk edit feature is very useful when I am working on multiple changes on a single data model and want to make multiple edits, as this saves considerable time.

I think a feature that allows me to add a bunch of 20 to 30 columns to a table at once would be helpful in erwin Data Modeler.

The UI is too complex, and a modernized UI would be beneficial for newcomers who want to understand it better.

I have been using erwin Data Modeler for the last one and a half years.

I did not use the AI capabilities yet because I do not trust these AI capabilities, and I am yet to understand their governance and security, so I do not have any confidence in that yet. I rate erwin Data Modeler an eight out of ten on a scale. I give it an eight because there are some features that create a bit of an issue. The UI is not modern, and it is loaded with so many features, which makes the UI complex for new users. Some small features that are missing right now, if added, could make it a ten. Overall, I think you are doing well.

My main use case for erwin Data Modeler is to create diagrams from databases before I start coding. I begin with the design of the databases.

For example, I used erwin Data Modeler in a particular project recently where it helped me organize data because the company previously used Excel spreadsheets. I had to perform the analysis and then create the tables in the database to establish the relationships.

I find it very useful because I can create code very quickly. For example, creating code for SQL Server, Oracle, or MySQL databases is very useful with this tool.

In my opinion, the best features erwin Data Modeler offers are that I can import or export my design, and after I finish with the database design, I can create the code, which makes the work easier. It is not only a design tool; it is more than that, and you can perform reverse engineering as well.

erwin Data Modeler positively impacts my organization because when I perform reverse engineering, it displays the visual model in just a few minutes, approximately five minutes. This allows me to see what the tables are, how they are connected, and the relationships between the tables. It is very useful because it does not consume a lot of time.

I think erwin Data Modeler could be improved when I have very large Oracle schemas. When I need to perform reverse engineering for databases with more than 500 tables, it becomes slow to render and move objects. I believe that would be an improvement.

Regarding erwin Data Modeler's AI capabilities, I think it would be great if it could suggest relationships, auto-document tables with AI-generated descriptions, or detect naming conventions. The competitors are starting to add those features. For governance, that is where erwin Data Modeler is actually strong because we use it as the single source of truth for our Oracle models, and it helps us with data governance.

I have been using erwin Data Modeler since I was studying at the university.

When I have to share files, we must share erwin Data Modeler files manually or use Mart server, and it has an extra cost and is complicated to set up. I gave erwin Data Modeler a rating of eight out of ten.

My use case for erwin Data Modeler is to identify the objects and keep the business details and object details into one pictorial diagram. Whenever a business wants to understand their operations, it is easy to walk through them with the PDF we have generated, which includes the links between the objects and functionality of the business and description of each column with business context. This tool is helpful for storing all this information.

My favorite feature of erwin Data Modeler is that we can export and import tables directly from the databases. It is easy to map from table to table and column to column.

In managing data across different environments, we are not dealing with the data in erwin Data Modeler. We use it to describe the relationships between tables and define how the data flows from one environment to another. For example, if we talk about a customer table, we define how many columns should be there and the data types and characteristics of that particular column and table. While we can store structure information at the mapping level, we are not managing data within this tool.

I would rate the visualization feature in erwin Data Modeler a six out of ten because the visualization is somewhat poor and some of the features are not user-friendly. You need to spend more time to make it a framework. There are areas where erwin Data Modeler can improve, such as scrolling and zooming in and out to see any particular columns. The visualization is average to above average, but not great.

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. The user interface resembles a 1998 Windows structure, so that can be enhanced.

I have experienced issues with stability in erwin Data Modeler because it does not have an auto-save feature. Whenever I do something and it crashes, I have to start from scratch. There is no automation such as in Word or Excel, where documents auto-save, and if something happens, they start from where they got saved. 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.

Scalability in erwin Data Modeler is good as it connects with multiple databases to pull existing table structures. I believe we can read the table structure from any type of database.

I have not contacted the technical support or customer support of erwin Data Modeler. Every product I have worked with captures business frameworks and detailed information. We have not encountered situations requiring customer care support. Erwin Data Modeler requirements function at a standard level, and when we seek something higher, we connect with the team for support.

Neutral

The initial deployment of erwin Data Modeler was easy. It is not overly complex. Those who can understand how Windows functions can easily complete the setup.

Regarding pricing, I am unsure what the exact price is for erwin Data Modeler, but I believe it is not useful for an individual. It is more targeted toward an enterprise level since organizations looking to store business information and relationship values may consider the pricing. I have never thought about that because we never tried to buy it. It is typically for those who need this tool on an enterprise level.

I have not used any alternatives to erwin Data Modeler extensively. I have used Data Vault, but it follows a completely different methodology and does not compare to this tool.

I do not see any integration capabilities in erwin Data Modeler with any projects I have worked on. There are no particular environments such as development, testing, and production. Since there is no end product to place in production, we handle only one environment. The main purpose of integration would be if any output criteria exist. However, the output products are essentially for documentation purposes. So far, in the projects I have worked on, there has been no integration involved with this tool. My focus has been on documentation, which is metadata about the business strategy.

I do not recall how long it took to deploy erwin Data Modeler because there is no deployment involved in my projects. As mentioned, there is no end product for development and production activities. We are merely keeping the business information, and the application of this product serves that purpose. The end result is a PDF representing business data flow.

I am a user of erwin Data Modeler, and I do not have any partnership with them. Partnerships typically involve enterprise levels, but I am a customer. Whenever I start working with a client, they show me the tool, and I begin using it. I would rate my overall experience with erwin Data Modeler an eight 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.

My main use case for erwin Data Modeler is to create logical, physical, and conceptual models.

I have a database in GCP where I want to extract the DDLs and do a reverse engineering on erwin Data Modeler to view the models, so we connected on the cloud, achieved the DDLs, and then proceeded to create and edit the models on erwin Data Modeler to show them to the clients.

The process of creating visual representations of data structures using erwin Data Modeler's enterprise-grade visualization feature starts by deciding on the business case, such as when I'm creating conceptual models.

I start with the conceptual models and then go on to the physical and logical ones, drawing the things in my head first and then starting to draw in erwin Data Modeler itself, using an Excel template and the wizard to import the tables I'm using for organization.

erwin Data Modeler has positively impacted my organization by being helpful to use, allowing us to demonstrate our models easily, being interactive and physical, while supporting reverse engineering.

By extracting DDLs, I can create a script in Excel to insert information about tables, columns, relationships, and other related details into erwin Data Modeler itself, which saves time because we just edited our existing Excel files to apply them to erwin Data Modeler.

The best features that erwin Data Modeler offers in my experience are the subject areas, where I can specify specific areas and separate them, and also the reverse and forward engineering functionalities.

With forward and reverse engineering, it is easy for me to extract DDLs from the model or to do the opposite, which really helps, and for the subject areas, I separate each by business needs, which is helpful visually and aids in organizing my work.

I think erwin Data Modeler can be improved by adding the option to separate physical and logical models when extracting, as currently, I can only extract them together, and implementing this solution would be easy for erwin Data Modeler.

I have been using erwin Data Modeler for almost three years.

In my experience, erwin Data Modeler is stable.

In terms of scalability, I find erwin Data Modeler pretty scalable and sufficient.

Regarding customer support for erwin Data Modeler, I did contact them by mail, and they were actually pretty helpful, opening my case and providing a very specific solution.

erwin Data Modeler is deployed in my organization on a private cloud.

The work of the DevOps team handled the infrastructure of deploying erwin Data Modeler, so I am not really sure about which cloud provider we use.

My advice for others looking into using erwin Data Modeler is to use the wizard and the options for extracting, reversing, or forwarding the engineering, as they are pretty helpful and represent a strong point of erwin Data Modeler itself.

As for the integration capabilities of erwin Data Modeler, I did not try them.

I also did not try if erwin Data Modeler helps improve data governance frameworks in my organization.

I would rate erwin Data Modeler an eight out of ten because of the points of consideration regarding improvements, and since I have not tried a lot of other models, I thought eight would be the sweet spot.

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.

My main use case for erwin Data Modeler is to model tables to deploy my ETL in production. When I create a pipeline to collect data and create a table, I need to model a table based on governance at the bank. In my work, I need to model it in erwin Data Modeler. I use it to model the table when I create a pipeline to collect data.

I cannot definitively answer how erwin Data Modeler has impacted my organization positively because when I started my job, erwin Data Modeler was already in use. I have never created a pipeline before using erwin Data Modeler because in my company it is mandatory to use erwin Data Modeler. Without erwin Data Modeler, it would be hard to define the DDL in tables.

erwin Data Modeler helps improve data governance frameworks because it helps my company map the tables. When I want to search for data, I search in erwin because in my company, we have one erwin instance in each group and team. We can organize the tables in erwin Data Modeler. erwin Data Modeler can make it easier to share information through good documentation and good modeling.

The impact of erwin Data Modeler in strategic decision-making within my organization is limited because we use it primarily to model the data, tables, and documentation.

The best features that erwin Data Modeler offers are the physical and logical models. This is the principal feature for me because when I create the logical model, I understand the naming conventions that governance creates for column names. The logical model is good for data modeling in erwin Data Modeler because I can understand when I receive a table created by another engineer. The logical modeling feature helps me understand the names, and this is helpful to me and to other engineers because it is simple to understand the conventions when you have a logical model.

Another valuable feature is defining the DDL in tables. I can define when a table should have partitions and when the table has a primary key or other DDL specifications for the table.

In my company, when I create the logical model, the physical model is not generated automatically. I believe that if erwin Data Modeler had this feature, it would be a good improvement to implement. When I create my naming rules and establish logical names, erwin Data Modeler could generate the physical names automatically. This would be a good feature to implement and improve, and I believe it would improve and accelerate my work.

erwin Data Modeler is very complex and unnecessarily complicated. The interface is not very intuitive, and simple tasks often require too many steps. The learning curve is higher than it should be.

I have been using erwin Data Modeler for three or four years.

erwin Data Modeler is stable in my experience, although it has some instances of crashes or downtime.

In terms of scalability, erwin Data Modeler is quite scalable because we can perform many modeling tasks for many tables. However, it is not easy to scale.

erwin Data Modeler is complex, and while it makes the job more complicated, the complexity is necessary because when we use erwin Data Modeler, we organize the tables and the data.

My experience with pricing, setup cost, and licensing for erwin Data Modeler is nonexistent because I am a data engineer. I do not work with architecture and only use the licensing, so I have never discussed the cost or pricing.

My advice for others looking into using erwin Data Modeler is to have patience because erwin Data Modeler is very complex, and you need patience to understand the frameworks since it has many frameworks and features which are not simple to understand. I would rate erwin Data Modeler a five out of ten.

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.

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.