erwin Data Modeler Reviews

My use case is mostly architectural design for our end-to-end deployment.

I like the best features mostly related to working with one of the Oracle tools that is OFSAA. When I make changes in the data model, even if the batch or any functionality resets it to zero, whatever changes I have done in the data model do not revert. It remains the same even if any database changes happen. No one can directly go and change the table structures or columns, therefore it is secure.

I see erwin Data Modeler has improved our data governance framework. My team mostly works as data modelers. When the model is ready for reporting or for the Power BI team, we give that end data to them for their further representation. We just create the model, replicate the functionality, and handle the logical aspects.

In erwin Data Modeler, areas that have room for improvement include performance improvements. I see that large models sometimes cause it to be slow when opening. Impact analysis can lag as well. Version control is another aspect. If we have developed a current version, it is not integrated with Git where we can easily compare different versions. UI modernization is also something we cannot utilize as it is primarily for development. Additionally, cloud-specific optimizations are needed when it comes to Snowflake or Databricks. When it comes to AI aspects, auto-suggestions for normalization or identifying primary, foreign, or surrogate keys are areas that can be improved.

I have been using erwin Data Modeler for more than four years and have significant experience with it.

Stability-wise, erwin Data Modeler scores an eight because it shows strong stability, especially in Mart repositories. While performance issues could occur with large models and improvements could be made, it remains reliable compared to other tools.

I rate erwin Data Modeler's scalability a seven. While it supports large enterprise models with multi-user collaborations effectively, performance can degrade during larger collaborations and requires tuning for optimal performance.

I rate erwin Data Modeler's technical support around seven or eight. This rating reflects my ability to effectively utilize the tool and get support for licensing issues, installation errors, or corrupted repositories end-to-end. Although complex issues may need several follow-ups, it still outshines other tools I have worked with.

Positive

I calculate return on investment based on total cost of ownership. If three engineers save ten hours each per month using erwin Data Modeler versus manual modeling, that equals three hundred sixty hours saved per year. The faster development and lower engineering cost lead people to adopt it. In larger organizations, the ROI tends to be more significant, and typical annual benefits can reach around $43,000 to $50,000.

Regarding pricing, it depends on the company. For a cloud or SaaS standard edition, it typically runs around two hundred to two hundred ninety-nine US dollars per month. For a workgroup edition, it comes to about three hundred ninety-nine dollars per month. Before purchasing, a free trial is available, and there are both term and perpetual licenses that allow for concurrent users. For larger teams leveraging a shared pool, it proves to be cost-effective.

I compare erwin Data Modeler with other solutions such as ER/Studio and believe it stands out as an enterprise-grade data modeling tool capable of serving different industries, such as finance, healthcare, and telecom. It supports cloud-native and hybrid warehouse integration, allows seamless creation of data catalogs or ELT/ETL pipelines, and can also be used for DevOps and CI/CD. Its visualization allows for documentation shared with stakeholders for better understanding, and it efficiently handles complex impact analysis without collapsing compared to other tools. It is also more trustworthy for integration and scalability.

My impression of the integration capabilities is positive. In a few of the projects, for instance, we connect the end reporting tool, such as Power BI.

I would describe the process of creating visual representations of data structures as having three types of data models: conceptual, logical, and physical data models. When I decide the design conceptually, logically I link how it has to be designed, and physically I actually create them. At that time, I perform the visual representation whether it is an entity relationship model or dimensional modeling or those types of things. Based on that category, I design the tables and columns and how the primary key and foreign key are linked to each other.

My impression of how effective erwin Data Modeler is in managing data across different environments is that mainly for RDBMS, I go for the entity relationship model. For document-based modeling, I work with MongoDB and NoSQL, and for dimensional modeling, I do work for Snowflake star schema for ETL-related tasks. Mostly these three types of modeling techniques I use.

My impression of the solution's role in enhancing collaboration among business, IT, and data teams is based on my overall nine years of experience. I started as a database developer, working with Oracle, SQL, PL/SQL, Unix, writing different stored procedures and functions for implementing banking functionality. As I move forward, whenever I design any table or database, I establish how the data relates to each other. This design and modeling part I do as a team with two to three others, and once the model is ready, we upload it into our front-end UI. Once it shows that the data model is successful, I check in our database whether the table or whatever items we have created have been reflected.

The main thing regarding how erwin Data Modeler helps ensure my data is AI ready and reliable is dependent on whether I have integrated that particular tool with any type of AI support initiatives or for AI/ML works. It can generate a starter data model or DDL script for me. If I have a GenAI script generation, it automatically generates the SQL and DDL script and validates it.

For deployment, I use erwin Data Modeler in the cloud primarily with Snowflake, and in Oracle, we have also migrated some tools there. Different object types are utilized across various parts. The cloud deployment is mainly through Amazon.

erwin Data Modeler can run in AWS environments and is mostly supported in a SaaS or cloud-based platform. It can also be installed on Windows server VM, container, or an EC2 instance and integrate with AWS databases such as Amazon Redshift, Aurora, or Athena via JDBC and metadata bridges.

When deploying erwin Data Modeler using AWS, it involves steps that can be easy or complex based on organizational needs such as security policies that do not allow SaaS. For self-hosted setups, I can easily launch an EC2 instance after logging into the AWS console, where I choose the server, storage, and subnet values, and install erwin Data Modeler while activating the license online, ultimately linking it to RDS or SQL server DB. Quest's hosted cloud offers a simpler deployment option without requiring infrastructure setups.

In my organization, approximately fifteen to twenty people work with erwin Data Modeler, with about seven to eight focused on data modeling. Multiple accounts and teams utilize it but in distinct ways, primarily for designing complex tables and presenting their connections to business stakeholders.

Maintaining this solution generally requires handling patches and version upgrades, which can be straightforward. However, database backups and user management within erwin Mart require regular attention.

For others looking into erwin Data Modeler, I recommend utilizing it based on my positive experience. Doing a proof of concept initially is beneficial, and focusing on data modeling fundamentals such as entity attributes and relationships will enhance usage. For beginners, it is crucial to gain practical knowledge in normalizing and naming conventions, while experienced users should focus on design and impact analysis.

I rate the effectiveness of the reporting capabilities for regulatory requirements highly, as we work with Basel II and Basel III concepts for regulatory reporting across different countries. Overall, I rate this solution a nine.

Public Cloud

Amazon Web Services (AWS)

Currently, I am an end-user of erwin Data Modeler, working as a full-time employee at TCS, not as a consultant. I interact with business customers and convert those concepts to developers. I occupy a middle position between the business and the developers.

My usual use cases for erwin Data Modeler involve converting the entire model from scratch, starting from the business concept through the conceptual model, logical model, and physical model. I handle relationship creation as well as subject area creation, and I perform all of these tasks in erwin Data Modeler.

The most valuable feature of erwin Data Modeler that I have found in my career is subject area creation. When I am joining tables in erwin Data Modeler, there can be more than 100 or 200 tables available, and they are joining with each other. This makes it difficult to understand the whole picture. However, if I segregate based on subject areas, that becomes the most valuable part. For example, if I define an ERP subject area, there may be sales involved with the ERP, manufacturing, point of sales, and HR. There are many models, so I prepare subject areas within the top of that model.

erwin Data Modeler plays a critical role in enhancing collaboration among business, IT, and data teams. Typically, analysts take information from the business and create system requirement and specification documents. My role is to convert the SRS into conceptual modeling and distribute it among developers. After that, the journey progresses from logical to physical. From the business concept through logical to physical, erwin Data Modeler depends on and covers every aspect within data modeling.

Areas of erwin Data Modeler that I think could be improved or enhanced include a few things. I have not worked in erwin for the past four to five years, but based on my 20 years of career experience, I worked with erwin one or two years on an earlier project and currently am working with it again. Based on my overall 20 years of career experience, I have worked with erwin modeling for four to five years. I am not a master of the tool, but I cannot identify significant flaws. The price should be reduced. That could be one area of improvement. Additionally, the licensing system could be enhanced. In our current project, there are five licenses within the business. If anyone is moving to erwin, the other person cannot enter the erwin solution. There should be a message indicating that five persons are involved in erwin, and you cannot use it at that time. However, that is a minor issue.

I have been working with erwin Data Modeler for four to five years. Based on my overall experience, which includes more than 20 years because I spent three or four years in business, my total business plus service experience is 23 years or more. As a modeler with this career span, I have worked four to five years with erwin Data Modeler. When I started, I transitioned from business into my career with Data Warehouse work. In the early 1990s, when Kimball's methodology was introduced in Data Warehouse technology, I began this journey. Overall, I have been working on Data Warehouse projects for 20 years.

My comment on how stable erwin Data Modeler is: I can rate it nine out of ten. It is the perfect modeling tool. In our current scenario, artificial intelligence has been introduced in many areas. I do not think erwin Data Modeler can be phased out from the data modeling perspective. Earlier, data modeling existed, and in the future, it will continue to exist. This should not be a concern.

Conceptually, erwin Data Modeler is quite scalable. The scalability question arises when we need to integrate anything that we are not getting from erwin Data Modeler. In that perspective, perhaps five to seven percent of integration is needed if we are not getting that feature from erwin Data Modeler. From the scalability perspective, it is good.

I have seen a return on investment when considering the cost and the results of the investment. If you are building a product, it is an investment of a company. Every product can be built with the help of the total structure of the modeling. If the modeling is compromised, then the entire structure will be compromised. This is very important for creating any type of data modeling. erwin Data Modeler is a primary part of the overall design. When I create a width of conceptual modeling, logical modeling, and physical modeling, there are many tables and objects available in the source, perhaps 1,000, 2,000, or 5,000. However, when creating a design in erwin Data Modeler or any type of modeling tool, approximately 80 percent of the tables can be removed. Actually, 20 percent of the objects can be determined as the whole lens of that project.

The process of creating visual representations of data structures using erwin Data Modeler's enterprise-grade visualization feature is straightforward. After completion of the model, I can easily export the model into a diagram. Features are available in erwin Data Modeler for this purpose.

My impression of the integration capabilities of erwin Data Modeler in connecting with erwin Data Intelligence and Enterprise Architecture tools is quite positive. Without erwin Data Modeler, I cannot create the data model on top of which the entire system depends. Without the data modeling tool, I cannot move forward. I have used the Enterprise Architect, Embarcadero Studio, and erwin Data Modeler. I have used most of the modeling tools available, but I found that erwin Data Modeler is the most suitable data modeling tool in our current industry. It is very expensive, but it is very good.

erwin Data Modeler is effective in managing data across different environments such as traditional relational databases, NoSQL, big data, and cloud platforms. In our current version, I have mostly used Databricks, SQL Server, and Oracle. I have used MongoDB, but not for the data modeling tools, so I do not have any practical concept about it. However, I have heard that the current version supports NoSQL. I have mostly used RDBMS for the modeling work.

erwin Data Modeler does help improve data governance frameworks. However, if you are asking about data governance, it is not limited to the erwin Data Modeler tool. We have to build most of the data governance components on top of it. If we want to secure the data in a proper way, we have to do data masking. If we want to secure the data, we have to implement proper access control. All of these elements are part of data governance.

erwin Data Modeler plays a significant role in strategic decision-making within TCS. Currently, I am working at TCS, and the models I have considered and created, as well as the data marts I have prepared, have made the customer very happy. As I mentioned earlier, without data modeling, no product can be built and no project can be built from scratch.

I can assess the effectiveness of erwin Data Modeler's reporting capabilities by saying that reporting capability means when I need to get any type of report, I can extract it from the menu options. That is not a problem. If I want to find the number of tables and the number of DDL scripts, I can easily extract this information. If I want to create or extract the data dictionary, I can extract it from there. That is not an issue. Many reports are available there. My overall rating for this review is nine out of ten.

I work for CVS with a pretty big database as a data modeler on the PBMs, the Caremark PBM side, which is the Pharmacy Benefits Manager. There's a retail side too for all the stores, but our data warehouse is for the PBM side of the business. Right now I'm working on moving all of our Teradata tables over to the cloud. We're redoing all the DDL from Teradata to BigQuery to GCP format, and we're rebuilding erwin Data Modeler files. As we're doing that, we're creating new erwin Data Modeler files in the GCP format for all the tables that we're migrating as we move them over. It's our only data modeling tool, so we use it for everything that we need it for.

I've used erwin Data Modeler for three major platforms: Oracle, Teradata, and now the cloud. I've never used it for a non-SQL database, just those three, and it works great for all three of them. I have another meeting right after this to talk about trying to get the next version of erwin Data Modeler, version 15, because I was told by someone at Quest that that one has full GCP BigQuery support. Right now, the version that we're using, 12.5, has support but it's not complete. There are some features that it's lacking, so I'm anxious to get the next version. Hopefully, this call will expedite that so that we can get a newer version of it that has more support for BigQuery. I've also used it to import Oracle SQL, Oracle DDL, and Teradata DDL, and then used a feature to convert that to GCP format, and that works pretty great. There are some things that it drops, but we have a workaround to get those things back, and I'll bet version 15 probably fixes some of that. But as far as it being able to work with those three database platforms and convert between them, it works really good.

I love the way erwin Data Modeler creates data models and presents them for our users. It's a great drawing tool and it represents the foreign key relationships, and you can easily drag those relationships to make the model easy to read. I think it's great. I've been using it a long time, and I think the way it presents the data in a visual format is great. It works fine, it's gotten better over the years, and it's really good now.

I can tell you that we're using it to manage CVS's data, which has some PHI and PII data, personal health information and personal identifiable information, which relates to HIPAA, the Privacy Act for medical information. We have to go through all of our tables, every column, and flag where it has PII data or PHI data and a couple of other flags that we use internally. I use the UDP feature, the user-defined property, for these extra data elements. erwin Data Modeler has a way that you can add identifiers for each column, and I use that feature a lot to track things that are specific to us, and we're using it for data governance. That's using an existing erwin Data Modeler feature to do that. There may be some data governance features built into erwin Data Modeler or some other related tool that we're not using, and if so, then I don't know about that. But I can tell you that we are using it to support our data governance needs, at least in a limited way using the UDPs for columns.

I write code and I write code accessing erwin Data Modeler's API, the Application Programming Interface, so that I can use Excel to update erwin Data Modeler and then get those updates and put them back into spreadsheets. The only thing I wish is that their API documentation was a little bit clearer and that it had better examples of successful code. To me, examples are worth a hundred pages of reference documentation. Just give me an example of how you use it, and that really helps. I know that's a nitpicking thing, but I wish their API documentation had a lot more examples of code that actually worked to do the things that they're talking about.

As far as erwin Data Modeler itself goes, when we have a lot of tables, I have some erwin Data Modeler files that have thousands of tables in them, up to 3,000 or 4,000 tables. When erwin Data Modeler files start getting that big, it takes a really long time, I'd say a minute or more, to open the file. Whenever I'm working in it, sometimes there are operations that also take a long time, so as erwin Data Modeler files get larger, the response time really slows down. An irritation is that every now and then, when I'm working and usually when I have multiple erwin Data Modeler files open at the same time, I get a glitch where a lot of the text fields get solid black, the first eight characters of column names might be blacked out with a rectangle. All I have to do is close erwin Data Modeler, shut it down, and bring it back up, and then everything is fine. It doesn't happen all the time, only occasionally, maybe once or twice a week, and those are the only two things I can say. The previous version of erwin Data Modeler used to crash unaccountably, but this one hasn't ever crashed on me, so it's been a lot more stable than the previous version that we had.

I started using erwin Data Modeler in 1998.

The previous version of erwin Data Modeler used to crash unaccountably, but this one hasn't ever crashed on me, so it's been a lot more stable than the previous version that we had.

If scalable means being able to handle more and more tables, then it just starts slowing down as we get more tables in an erwin Data Modeler file. It scales; you just have to be patient with it as it opens up those big files.

I've emailed support and they've always been responsive to me.

Positive

erwin Data Modeler was already there when I started; I don't do the deployment. CVS, a giant corporation, has a team that packages up applications and makes them available for all employees, and then another team that pushes them to your PC. I am not in that group that does the deployment of the tools, and I really never have been. It's always just been pushed to me on my laptop wherever I was, so I really can't answer that question. I assume it's not too hard, but I really don't know.

There is a corporate team above me that decides on what tools we use as a company. I don't know what they're doing for that or how they make those decisions, but we haven't integrated erwin Data Modeler with other enterprise architecture tools. It would be tough for me too because it's not my role to do that. I've recommended before that we could use it especially to integrate it with Informatica to get some data lineage going, but we haven't done it, unfortunately.

I haven't tried integrating erwin Data Modeler with other enterprise architecture tools, and there's a corporate team above me that decides on what tools we use as a company. I don't know what they're doing for that or how they make those decisions, but we haven't done it, and I haven't done it. It would be tough for me too because it's not my role to do that. I've recommended it before.

I rate the support team a 10. They've always been really helpful and prompt. I would rate erwin Data Modeler overall a nine. I'm sure there are some things that can always be fixed, but it's been a great tool. I've been using it most of my career, and my overall rating for this solution is 9 out of 10.

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 used erwin Data Modeler for approximately two to three years on a project. I used erwin Data Modeler for multi-level data modeling, conducting conceptual, logical, and physical data modeling within it. Conceptual modeling involved high-level entities and business terms and relationships. Logical data modeling included normalization and attribute-level specifications, as well as business rules. Physical data modeling involved data types, database-specific constructs, and schemas. erwin Data Modeler's ability to maintain model-to-model traceability is one of the biggest strengths.

The process of creating visual representations of data structures using erwin Data Modeler allows you to see everything you are doing. When you are working with the data, you are actually seeing the visual representation, and you have visuals to see what you are going to do and what has been done so far. It's not just attempting to make sense of a lot of data, but the way the data is organized and you have a visual of that organization helps a great deal in terms of trying to remember what you did and trying to retrieve the information. If you have worked through the entire process, it's a very significant advantage.

I think about the integration capabilities of erwin Data Modeler and connecting with erwin Data Intelligence and enterprise architecture tools. Model navigation was tree-based, it had a zoom pan, auto layout, entity-attribute filtering, views, and sub-diagrams. erwin Data Modeler was stable for most database engines, but I recall it became slow when the models were extremely large, containing more than a specific number of database objects.

In managing data across different environments, erwin Data Modeler supports most major relational databases such as Oracle, SQL Server, PostgreSQL, and MySQL. It can read metadata directly from live databases and can help visualize legacy systems or systems that are not properly documented. I think that erwin Data Modeler is a very reliable tool for modernization and migration projects.

Regarding stability, I have not seen any lagging, crashing, downtime, or any sort of instability; it was very stable for most of the database engines.

For the review, I would assign an eight because it has its own limitations. It has a very steep learning curve, limited support for NoSQL or streaming systems, and potentially a high licensing cost. I assume not many companies opt for erwin Data Modeler for their data modeling, and I do not know how dated the API is for erwin Data Modeler or whether it updates regularly to include all the upcoming technologies.

erwin Data Modeler became slow with large models, so we had to be mindful of not creating very large models within it. I do not have too many maintenance-related tasks.

For standardization, it was very good, such as creating naming conventions, data type domains, and rule enforcement to strengthen data quality. erwin Data Modeler had a very good standardization infrastructure and supported a controlled multi-user environment with check-ins and check-outs. It was good for hybrid as well as on-premise or cloud data ecosystems. When I say that it was good for cloud data ecosystems, I am assuming that it is definitely very scalable.

I did not try contacting their technical support; I used to contact my IT support instead.

Neutral

I have not used any alternatives to erwin Data Modeler and cannot compare it with anything else. In data modeling, I have not had too many projects to work on, and the other tool I used for data modeling was Lucidchart, which is very different from erwin Data Modeler and not even comparable.

I am not the right person to ask about the pricing of erwin Data Modeler because I was just a user. I would rate this product an eight overall.

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.

Public Cloud

Other

As a data modeler of one medium size Bank in Mozambique, I use the solution to respond to main requirements and I am responsible for building our data warehouse, so I need to use this tool to design the data models, logic, and physical data models.

I use this tool to integrate DDLs into a repository for the Mart server, utilizing it to integrate data from one source to another, while erwin Data Modeler is primarily for creating the models themselves. For ETLs that load data, I use Talend Open Source.

In my organization, I work within a group that involves two or three people using erwin Data Modeler, while the our mother company located in South Africa has more than 20 users.

erwin Data Modeler's best features include its ease of documentation, for example, data lineage, which is easy to document in the tool, and the ability to generate scripts, alter scripts, and create scripts. I find it easy to compare two models if I want to verify that the model I designed matches the model implemented in the database. The comparison between models and data lineage documentation make it a good tool.

Migrating DDLs using erwin Data Modeler is easy because I just connect to the database and generate the data model from what is already implemented, making the process straightforward.

By not having to depend on data modeling teams to send DDLs, if I have a database with 50 tables, using the tool, it takes less than three minutes to view the entire database structure, relationships, primary keys, and field types, whereas building it manually could take days or weeks, so the tool significantly improves this task.

erwin Data Modeler's ability to generate database code from a model for a wide array of data sources saves time in development, as utilizing the solution allows me to accomplish tasks in minutes compared to the extended time required for manual processes.

Regarding code generation, the functionality is well-organized, generating simple, easy-to-interpret code that ensures accurate engineering of data sources.

On data governance, while I do not explore this subject deeply, I have tried some features, such as defining organization-specific naming rules for fields, allowing me to control naming conventions using erwin Data Modeler, which includes functionality to check if the fields follow predefined rules.

While I do not have knowledge about pricing for erwin Data Modeler, I think it could improve by having a feature that allows the publishing of models, similar to how Power BI allows for dashboard publishing for different users within an organization, not just data modelers.

I have been using erwin Data Modeler for two and a half years.

I would rate the stability of erwin Data Modeler as an 8, considering I have not experienced significant downtime, bugs, or glitches.

erwin Data Modeler is scalable. I would rate its scalability as an 8.

I have not required technical support for the past two years because I have been able to accomplish everything I need, so I cannot comment on it.

Negative

In my experience, having used only two tools, including erwin Data Modeler and a tool named Design, I find erwin Data Modeler to be superior due to its greater functionalities, ranking it among the top three best solutions for data modeling.

The transition between legacy systems and modern platforms using erwin Data Modeler is seamless as long as I have the appropriate connector for the legacy system, making integration consistent regardless of system type.

I would recommend erwin Data Modeler to other users because it is one of the best tools on the market, effectively covering about 90% of data modeling needs.

The importance of DevOps GitHub integration lies in the tools facilitating script generation to design physical tables; however, it is crucial to understand SQL to address potential errors, which means the tools improve development time but I still need to know what I am doing.

erwin Data Modeler does not validate data; it focuses on validating the model I build, meaning the rules used to create the model are validated, but for data validation, other tools are necessary, as the primary purpose of erwin Data Modeler is to build models: conceptual, logic, and physical.

I would rate the solution as an eight.

I was using erwin Data Modeler in my company to create tables, columns, and structures in SQL.

erwin Data Modeler is well organized, and the screen layout is intuitive. The overall positive impact and measurable benefit I experienced from working with it is that controlling the new tables or relations that we were adding was clearly better. The view looked better in erwin Data Modeler than creating them directly in SQL, and this was more controlled than it could be if we created something directly in SQL.

I would like to see improvements in other aspects of the data modeler apart from the errors with the databases. The time that it took to download the new XML was considerable, and if this could be faster, that would be beneficial, though I am not certain if this is related to erwin Data Modeler or our server.

What I did not like was that sometimes while I was creating relations, I was not getting errors. The errors only appeared when I tried to upload the model into a new database, which took a lot of time because I was creating a model, reproducing XML, and then trying to add the XML in the database. At that moment, I was getting the errors, so this cost us a lot of time sometimes.

I have been working with erwin Data Modeler for around two to three years.

I personally have not had any crashes, downtimes, or performance issues with it.

I do not think there are scalability issues. As far as I can recall, if the things I mentioned before could have progressed, it would be better, but I cannot speak to other aspects. Some months have passed since I have not worked with it, so I cannot say with certainty.

Regarding erwin Data Modeler technical support and customer service teams, the experience could have been better. Sometimes I was asking questions and receiving repetitive questions from the team. They were responding to my questions with another question, so I lost a lot of time on some things that I remember we were asking about, and they were not really fast. This could be a better performance.

I have not used any different products of the same kind prior to adopting erwin Data Modeler. The other solutions I have used were only directly on SQL, so I have not used another data modeler program.

Regarding the initial setup process, the experience with the deployment aspect was not complex. I can say it is a friendly application, and you can learn it really fast. It is very friendly. When I started at the beginning, a colleague who was senior taught me, as I was a junior at that time, and I learned it really fast. I can say it is very friendly.

I did not evaluate any other options or solutions available in the market. The company decided to go with erwin Data Modeler, so I cannot speak to alternatives.

I would recommend erwin Data Modeler as a product and solution if companies want to have more control over the new things that they want to add in a database. However, I will not recommend it if they want to save money and create everything in SQL, as there are benefits, but you can also do it without erwin Data Modeler. I have no idea regarding missing features in erwin Data Modeler that I would like to see included in the future, and I have no idea about any advice or recommendation that I would share with other organizations considering erwin Data Modeler. My overall review rating for erwin Data Modeler is seven.

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.

On-premises

Other

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.

On-premises