erwin Data Modeler by Quest Reviews

We are using it for a very specific use case, and it works pretty well for us. We do all of our database modeling based on this tool, and it is a repository of all data models in our business intelligence ecosystem. The logical representation of our metadata and anything that is created in a database, such as tables, is in it. 

It is an on-prem workgroup. We have a workgroup server that hosts our model.

We utilize it for its cross-database capability and logical representation of the data model. We have recently started to use its collaboration features, and we also use it to define all our relationship constraints and referential integrity within our data model. So, a lot goes out of it.

It has standardized our practices. For example, all customer-related entities and attributes have to follow a certain naming convention. It has helped in standardizing the process of creating our data models so that when we go and explore the data, we can combine them in a way in which we are confident of producing the right results. It has made a lot of difference in terms of naming standards, processes around our metadata, and the schema in which we create a database. We have a proper template to put the information through a well-structured data model. It helps users in getting the maximum value of the information that is available in the BI ecosystem. erwin Data Modeler makes it very simple and easy to navigate our very complex data.

Its visual data models are very good and helpful for overcoming data source complexity and enabling understanding and collaboration around maintenance and usage. We have a complex business environment where we have retail and supply chain space for distribution. There are a lot of cases where we use the models for customer promotions and events and loyalty systems. Different data modelers can do their own subject areas, and then they can bring them together in a workgroup workspace. It has allowed us to collaborate and distribute the data modeling work. Previously, it used to be very single-threaded. Now, a lot of different teams can run their own modelers, and then, later on, integrate them, which is very useful. It is also very useful in the database migration process. You can take a logical model and seamlessly transfer it over to the database. That's very useful as well. 

We use its modeling support for Snowflake Cloud. We don't use it in any special way. We use it the way we use an existing on-prem database. It just needs to follow Snowflake conventions, which it does. We have a standard logical model that can then translate to a physical model for any database we choose, and that's where erwin has been very helpful. We can set those naming standards, and it also does logical to physical translation seamlessly. This support for Snowflake is helpful. We have enough help to port our model from DB2 to Snowflake in terms of model creation. It has proven very helpful that way.

It can create table structures across a wide variety of sources, which is very useful for us. It cuts the development time of our database code quite a bit. Otherwise, we would have to rely on Excel sheets. Currently, our average project size is anywhere from 3,000 to 4,000 hours, and out of that, we spend around 5% on data modeling. If we didn't have this tool, it will take almost twice more time for any project.

It allows us to create logical data models. We can represent a database model in business terms, which is very useful for us. 

It supports a wide variety of databases, including the latest ones. We have chosen to go for a cloud-based database, and it supports that, which is very useful. 

It is very useful for maintaining relationships between tables. We can put constraints and foreign key-primary key relationships into the model, and it gets translated into the physical database seamlessly. 

Workgroup is another useful feature to store and share the models with the team for collaboration. 

In terms of improvements, support could have been better in terms of installation, especially of workgroups. We struggled quite a bit to get it up and running. Collaboration could have been better from an installation perspective, but it is trivial as compared to what we use it for. Other than that, I don't have much feedback. It works pretty well, and the fact that we've been using it for more than a decade shows that it is quite solid. 

In terms of new features, it would be great to have a cloud base. We should be able to put it on the cloud for better collaboration and data models sharing.

I have been using this solution for more than a decade.

It is very stable.

It is fairly scalable. We really haven't pushed it to the limit with respect to scalability, but we haven't found any issues.

Currently, we have around 20 users. They are mostly data modelers and data engineers. We have plans to increase its usage as deploy additional systems in our business unit. So, there are plans to scale up, but not in the immediate future.

I have interacted with their technical support. I would rate them an eight out of 10.

I have been in this company only for two years, but from the licensing, I know it has been more than 10 years. I am not aware of any other tool being used previously.

There wasn't a lot of stuff. When things didn't work, we had to go and figure out why this isn't working and which ports should we open. There was a lot of back and forth communication with their support, and they were very helpful, but it gets pretty difficult when something that could be done in one to two hours takes you longer than that. It took us a few weeks to get it right, but once it started working, it was pretty seamless.

There was no implementation strategy. You just download an installable and install it. The problem is that it requires a database, and it requires a particular configuration. All this is documented, but it doesn't work the way it is documented. So, it took time for us to figure out, "Hey, this thing is not working. Why is it not coming up?"

For maintenance, we don't have anyone. For the deployment of the workgroup, it took just one person. My data engineering lead just went and did it all by himself. It is a pretty simple product. It just took us a while to figure it out, especially the collaborative tool. Generally, it is supposed to take half an hour for one person.

We installed it ourselves. We did not use anybody to install it, maybe that's why it took us longer.

I don't have the metrics, but I would say we have seen an ROI. It has brought down the cost of implementation in terms of manpower. It might have saved us thousands of hours. It could also be more than a hundred thousand hours. 

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources make the cost of the tool totally worth it.

There are no costs in addition to the standard licensing fees.

In general, for its purpose or use cases, it is the best tool in the market. It does its part in terms of metadata, but we have other challenges that erwin cannot resolve. We have a large pool of legacy data sources that are not labeled, and erwin really can't help there. I don't see any other tool filling that space unless we go for a catalog, which is a different product space altogether. erwin can process the legacy files, but we're just not using it for that because we don't have the bandwidth.

You need a skilled modeler to start off. It really depends on what kind of organization is implementing it: small scale, mid scale, or big scale, but collaboration really works. It is a very good tool, but proper training would be required to take full advantage of the tool. It helps to do a lot more on the job. You would need a lot of discipline before you start using the product. The standards and governance should be put up front before it can be utilized effectively.

The biggest lesson that I have learned from using this solution is that it cannot resolve governance issues. You need to have proper standards in place before you start using this tool. Bad processes lead to bad outcomes. The tool will help you shepherd those processes, but it doesn't solve them. So, you need to have proper process governance and standards. You need to make the tool enforce those processes and standards. You should have proper controls on the data inside in order to get the best results. Governance and process discipline are pretty important. 

On the database side, I come from organizations where some people follow one standard, and other people follow another set of standards, and if we use the same database and tools, then you get a mess. That's where the process discipline comes in for unified governance, which has got nothing to do with the tool. It has everything to do with how the organization is structured. The tool will help you to control that.

I would rate erwin Data Modeler a nine out of 10. If it can be on the cloud without any installs, that would make it a 10.

I am using it for database design. I am using it to architect and generate one database platform from another. It involves reverse engineering and SQL generation.

Its biggest benefit is the conversion from one database platform to another database platform and reporting.

It provides flexibility with the code. You can change the code as you want. Basically, you can change SQL based on what's best for your project.

There are some bugs here and there. The default code that comes with the customizable packages is a bit buggy on some platforms such as PostgreSQL. erwin has its own language in the backend, and the packages that come for PostgreSQL are a bit buggy. They should fix them.

It would be nice to have it on the Linux platform, not just Windows. If they can support Linux, there would be a huge market for it. 

Currently, we can import only 80% of features from other platforms. We would like to be able to get the remaining features. These import tools or plugins are not from erwin. They are from different companies. Ideally, erwin should take them over and make some of those better.

I have been using this solution for about a year and a half.

It is pretty stable.

It is very scalable. This is something very nice about it.

We have three users who use this solution. They are from the database administration team. For its administration, we have the database administration team lead.

It is used for database architecture and design. We use it only when we have to make some changes. We then produce documentation of the database design changes. As long as there are changes to be made, it is in use. Otherwise, it is not in use.

Their technical support is very good.

We used System Architect from UNICOM, which was outdated. 

It was very straightforward. The deployment took three days, which included evaluating our upgrades. Installing and configuring erwin took only 10 minutes.

We did it on our own.

We have not got a whole lot of ROI. We use it restrictively for database administration. I know it can be used for other plans of architects, but in our case, it is not fully used.

We didn't go for a subscription. It was a one-time fee. I don't understand who does subscriptions on such solutions. PowerDesigner comes with yearly subscriptions, and I can't understand how that is possible. Who in the world keeps on changing the database engine? Once you have such an application, you cannot just upgrade it like your phone. So, I cannot understand how they're pushing this.

erwin has this option where you pay a one-time fee and you have the license for six years, which makes sense because I don't upgrade my database engine every other year. I have an application that depends on it. This is something weird about PowerDesigner. 

There are no additional costs beyond the standard licensing fee.

We also evaluated PowerDesigner. It has an excessively high price. It is ridiculous. It was not that the company could not afford it, but the price was just unnecessary.

It is a very good product if you want to import existing designs. It is a tremendously flexible product for reverse engineering and database generation.

I would rate it an eight out of 10. The main reason is that it has lots of features. It is extremely flexible, but some of the areas need a bit more debugging, testing, and fixing.

I am responsible for both a combination of documenting our existing data models and using erwin Data Modeler as a primary visual design tool to design and document data models that we implement for our production services.

My primary role is to document our databases using erwin to work with people and ensure that there is logically referential integrity from the perspective of the data models. I also generate the data definition language (DDL) changes necessary to maintain our data models and databases up to our client requirements in terms of their data, analytics, and whatever data manipulation that they want to do. I use erwin a lot.

It is either installed locally or accessed through a server, depending on where I have been. I have had either a single application license or pooled license that I would acquire when I open up erwin from a server.

We get data from many different sources where I work. We have many clients. The data is all conceptually related. There are primary subject area domains common across most of our clients. However, the physical sources of the data, or how the data is defined and organized, often vary significantly from client to client. Therefore, data modeling tools like erwin provide us with the ability to create a visual construct from a subject area perspective of the data. We then use that as a source to normalize the data conceptually and standardized concepts that are documented or defined differently across our sources. Once we get the data, we can then treat the data that has been managed somewhat disparately from a common conceptual framework, which is quite important.

At the moment, for what I'm doing, the interface to the physical database is really critical. erwin generally is good for databases. It is comfortable in generating a variety of versions of data models into DDL formats. That works fine.

What has been useful, I have been able to reverse engineer our existing data models to document explicitly referential integrity relationships, primary/foreign keys in the model, and create ERDs that are subject area-based which our clients can use when working with our databases. The reality is that our databases are not explicitly documented in the DDL with primary/foreign key relationships. You can't look at the DDL and explicitly understand the primary/foreign key relationships that exist between our tables, so the referential integrity is not easily understood. erwin has allowed me to explicitly document that and create ERDs. This has made it easier for our clients to consume our databases for their own purposes.

Its visualization is the most valuable feature. The ability to make global changes throughout the data model. Data models are reasonably large: They are hundreds, and in some cases thousands, of tables and attributes. With any data model, there are many attributes that are common from a naming perspective and a data type perspective. It is possible with erwin to make global changes across all of the tables, columns, or attributes, whether you are doing it logically or physically. Also, we use it to set naming standards, then attempt to enforce naming standards and changes in naming from between the logical version of the data models and the physical versions of the data models, which is very advantageous. It also provides the ability to document primary/foreign key relationships and standardize them along with being able to review conceptually the data model names and data types, then visualize that across fairly large data models.

The solution’s visual data models for helping to overcome data source complexity and enabling understanding and collaboration around maintenance and usage is very important because you can create or define document subject areas within enterprise data models. You can create smaller subsets to be able to document those visually, assess the integrity, and review the integrity of the data models with the primary clients or the users of the data. It can also be used to establish communications that are logically and conceptually correct from a business expert perspective along with maintaining the physical and logical integrity of the data from a data management perspective. 

We are not using erwin's ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync to the fullest extent. Part of it is related to the sources of the data and databases that we are now working with and the ability of erwin to interface with those database platforms. There are some issues right now. Historically, erwin worked relatively well with major relational databases, like Oracle, SQL Server, Informix, and Sybase. Now, we are migrating our platforms to the big data platforms: Hadoop, Hive, and HBase. It is only the more recent versions of erwin that have the ability to interface successfully with the big data platforms. One of the issues that we have right now is that we haven't been able to upgrade the version that we currently have of erwin, which doesn't do a very good job of interfacing with our Hive and Hadoop environments. I believe the 2020 version is more successful, but I haven't been able to test that. 

Much of what I do is documenting what we have. I am trying to document our primary data sources and databases in erwin so we have a common platform where we can visually discuss and make changes to the database. In the past couple of years, erwin has kind of supported importing or reverse engineering data models from Hive into erwin, but not necessarily exporting data models or forward generating the erwin-documented data models into Hive or Hadoop (based on my experience). I think the newest versions are better adapted to do that. It is an area of concern and a bit of frustration on my part at this time. I wish I had the latest version of erwin, either the 2020 R1 or R2 version, to see if I could be more successful in importing and exporting data models between erwin and Hive.

erwin generally fails to successfully reverse engineer our Oracle Databases into erwin data models. The way that they are engineered on our side, the syntax is correct from an Oracle perspective, but it seems to be very difficult for erwin to interpret. What I end up doing is using Oracle Data Modeler to reverse engineer into the Oracle data model, then forward engineer the DDL into an Oracle syntax, and importing that DDL into erwin in order to successfully bring in most of the information from our physical data models. That is a bit of a challenge. 

There are other characteristics of erwin, as far as interfacing directly with the databases, that we don't do. Historically, while erwin has existed, the problem is the people that I work with and who have done most of the data management and database creation are engineers. Very few of them have any understanding of data modeling tools and don't work conceptually from that perspective. They know how to write DDL syntax for whether it's SQL Server, Oracle, or Sybase, but they don't have much experience using a data modeling tool like erwin. They don't trust erwin nor would they trust any of its competitors. I trust erwin a lot more than our engineers do. The most that they trust the solution to do is to document and be able to see characteristics of the database, which are useful in terms of discussing the database from a conceptual perspective and with clients, rather than directly engineering the database via erwin. 

erwin is more of a tool to document what exists, what potentially will exist, and create code that engineers can then harvest and manage/manipulate to their satisfaction. They can then use it to make changes directly to our databases. Currently, when the primary focus is on Hive databases or Hadoop environment, where there is no direct engineering at this point between erwin and those databases, any direct or indirect engineering at the moment is still with our Oracle Database.

I have been using the solution on and off for 20 to 30 years.

It is pretty stable. Personally, I haven't run into any real glitches or problems with the output, the ability to import data when it does work correctly, the export/creation of DDL, or generation of reports.

We are trying to upgrade. This has been going on now for several months. We're trying to upgrade to the 2020 version. Originally, it was 2020 R1, but I think at this point people are talking about the 2020 R2 version. Now, I'm not part of our direct communications with erwin in regards to Data Modeler, but there are some issues that erwin is currently working on that are issues for my company. This have prevented us from upgrading immediately to the 2020 version.

This gets down to how you do your data modeling. If you do your data modeling in a conceptually correct manner, scaling isn't an issue. If you don't do your data modeling very well, then you are creating unnecessary complexities. Things can get a bit awkward. This isn't an erwin issue, but more a consequence of who is using the product.

In the area that I'm working right now, I'm the only user. Within the company, there are other people and areas using the solution probably far more intimately in regards to their databases. I really don't know the number of licenses out there.

The problem is that our issues are related to interfacing erwin Data Modeler with the Hadoop Hive environments. The issues have always been either what I was trying to do was not fully supported by our version of erwin Data Modeler. People have certainly tried to help, but there's only so much that they could tell me. So, it's been difficult. I am hoping that I can get back to people with some better answers once the newest version of erwin is available to us.

The people who were previously responsible for the database development were very good engineers who knew how to write SQL. They could program anything themselves that they wanted to program. However, I really don't think that they really understood data modeling as such. They just wrote the code. Our code and models are still developing and not necessarily conformed to good data modeling practices. 

In the past, I was involved in the initial setup. In traditional environments, it sets up pretty easily. In my current environment, where I'm trying to get it as intimately integrated with our big data platforms as possible, I'm finding it quite frustrating. However, I'm using an older version and think that is probably a significant part of the problem.

In other environments where I've worked, the solution’s ability to generate database code from a model for a wide array of data sources cuts development time. In this environment, erwin is not very tightly integrated into the development cycle. It is used more for documentation purposes at this point and for creating a nascent code which down the road gets potentially implemented. While it's not used that way at my current company, I think it would be better if it were, but there is a culture here that probably will prevent that from ever occurring.

An issue right now would be that erwin doesn't have a freely available browser (that I am aware of) for people who are not data modelers or data engineers that a consumer could use to look at the data models and play with it. This would not be to make any changes, but just to visually look at what exists. There are other products out there which do have end user browsers available and allow them to access data models via the data modeling tool.

There is another tool now that people are using. It is not really a data modeling tool. It is more of a data model visualization tool, and that's SchemaSpy. We don't do data modeling with that. You get a visualization of the existing physical database. But that's where the engineers live, and that's what they think is great. This is a cultural, conceptual, understanding issue due to a lack of understanding and appreciation of what good data modeling tools do that I can't see changing based on the current corporate organization. 

It is the only meaningful way to do any data modeling. It is impossible to conceptualize and document complex data environments and the integration between different data subject areas. You can write all the code or DDL you want, but it's absolutely impossible to maintain any sort of conceptual or logical integrity across a large complex enterprise environment without using a tool like erwin. 

You want to look at what you are trying to accomplish with erwin before implementing it.

• Does the product have the ability to support or accomplish that?
• Based on the technologies that you have decided you want to use to manage your data, how intimately does it integrate with those technologies? 

From my perspective of using the traditional relational databases, I think erwin probably works pretty well. 

For the newer database technologies, such as the Hadoop environment databases, it's not clear to me how successful erwin is. However, I'm not talking from the perspective of somebody who has been aggressively using the latest version. I don't have access to it, so I'm afraid my concerns or issues may not be valid at this point. I will find out when we finally implement the latest erwin version.

I would give the solution a seven or eight (out of 10).

erwin is deployed on individual desktops and the individual users install it or have a help desk person install it for them.

Our primary use case is for during any type of project development or maintenance and application maintenance, we go through a process of modeling our data before it gets put into the database. We interact with the application development teams to determine what their requirements are and build the data models, and then turn them into actual physical database items.

erwin has definitely helped us improve our enforcement of standards and database design best practices. Before we really started using the tool or having a data modeling type of team, application development efforts all had their own database structures. Developers tend to not be too concerned with the data. They just want to make everything work for their application as easy as possible. Having the tool and having a team built around it has really helped us make sure that we're following the best normalization processes, we're not duplicating data, and we have a standard naming scheme that everybody has to follow.

The modeling portion of the tool is the most valuable. There are some notes, naming standards, and other functions that we use as well. There's a whole boatload of functionality in this thing and we use maybe 10% of it. It seems to be pretty common that not all the functionality is fully utilized. But it's got gobs and gobs of stuff that you can implement if you so choose to.

We've definitely expounded on the amount of features we use. They've built in some automated naming standards that have been really helpful for us. That's probably the biggest leap we've used. We've always used the comments and notes features, but the automated naming features have been very helpful.

Its ability to overcome data source complexity and enabling understanding and collaboration around maintenance and usage is extremely helpful because they give a visual to not only developers and database administrators, but the user base themselves. So the typical user isn't going to understand database functionality. Being able to show them a picture of how their data is actually going to look in the database is very helpful for their understanding of what we're trying to do with their data.

erwin's ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync is very good. We utilize that service quite a bit. The one drawback is if you have an extremely large complex model, the compare process can take quite a bit of time, more than four hours. 

Its ability to generate database code from a model for a wide array of data sources cuts development time. The fact that you can generate the DDL correctly from the model saves us a bunch of time. I would say it saves us around 40% to 50%. So even though you can generate the DDL, you still have to go in and tweak it a little bit. 

The only real complaint I have is the time it takes to do a database comparison on a large model. If they could speed that up, that would be the only thing I can think of that needs improvement.

We've been using erwin since about 2000. We were using another product before, but it was way too cumbersome, so we switched to erwin.

Stability is excellent. It's been a solid product for years and I don't expect it to change.

It's extremely scalable. Our environment has hundreds of tables. 

We have five data modelers using the tool. That's the team that actually works with the app dev and DBAs to actually come up with the database design. Then we have another five users that act more in a read-only type of mode. They just want to look at the data models, but they don't actually do any of the design work.

Their support was excellent. Typically it has to do with going through the upgrade process. If we have an issue, we'll reach out to them. The other thing we've had to reach out to them about was the time it was taking to do a data comparison on our extremely large model to the actual physical database. They were very helpful and very professional.

We don't typically have problems transitioning between the models. We did last time, but it was actually an error on our end. It wasn't an error on the erwin end.

We were using Cayenne. We switched because it was cumbersome.

The initial setup is typically straightforward. Just follow their instructions and everything goes pretty smoothly.

For the Data Modeler portion itself, on each desktop, the setup took around half an hour, and we have around 10 desktops.

We didn't necessarily have a deployment strategy. We just gave the product to anybody that thought they needed it and let them run with it.

For maintenance, we need one person, but it's definitely not a full-time job. It's just adding and subtracting users and going through the upgrade process when we do that. As far as installation, everybody basically installs it themselves. We don't require a full-time person for that either.

We have a team around it, so if we add our data modeling team up, we use it about six hours a day per person. That would be about 18 hours a day for those guys. The read-only users rarely use it, so they're pretty insignificant. 

We probably only use 10% to 20% of the functionality and I don't see us expanding on that a whole lot. There's a lot of neat little things in there, but we don't have time to implement them all. There's some overhead that goes with those functions that we choose not to undertake.

Since we got a new guy on our team, he's gotten into some of those functions and has been able to utilize some of that stuff some more. We're actually probably closer to 30% or 40% of the functions at this point. We're not thinking about expanding because of the overhead. 

I don't remember what our costs are. I know they just recently switched from a per seat type of licensing to a concurrent user type of licensing agreement, which is neither here nor there. I don't think it has increased or decreased the cost at all, but it's not obtrusive or invasive as far as the cost goes. It's fairly affordable.

There are also internal costs if you have hosted on-prem because you have to have a server and database to stand it up on.

We didn't evaluate another solution because I had used erwin at another location and was extremely familiar with it. And I had also used Visio and some more manual-type methods like Visio. At the point that we decided to switch over, I was confident that erwin was the best solution out there.

erwin is by far the best tool I've ever used. 

My advice to somebody considering this solution is to go for it. It's easy. The functionality is fantastic. It's easy to pick up. It does basically everything you could want it to do.

The automation of reusable design rules and standards has helped us immensely once we implemented it because having the automated naming standards and things like that, we don't have to go in and think about it. We don't have to go in and physically type it. Between generating the DDL and getting it into physical implementation was saving us 40% to 50% of time. It's because of those automated features that that's happening as opposed to having to sit there and type out the DDL from scratch, it saves a ton of time.

It produces a time savings of about 40%.

The accuracy and the speed of this solution in transforming complex designs into well-aligned data sources absolutely make the cost of the tool worth it.

My advice would be to let things evolve over time. Start with the basics first. Just get into the ERD functions first and then start implementing some of the automated naming standards and things like that as you go. Otherwise, if you try to dive into the whole thing, you're just going to get overwhelmed because the product is so deep as far as features go. It's extremely intuitive. As far as the basics go, as far as getting your ERDs established, it's probably the easiest tool I've ever used. If you understand the basics of database design, it's extremely natural. If you have no clue about database design, then your learning curve is going to be large no matter what tool you pick. But erwin definitely cuts that learning curve down just because of its intuitiveness.

Once you start diving into the automated feature sets like naming standards and things like that, the learning curve there is a little steeper, but it's still not too bad. For a brand new person, if you try to delve into the automated stuff and all the additional functionality, you're just going to get overwhelmed and feel that there is too much overhead. But you don't need to implement all those features right off the bat.

I would rate erwin a ten out of ten.

The whole purpose of the erwin tool is for the designing of databases. We use it for our conceptual, logical, and physical database modeling.

We've been using this product as long as I can remember at our company, so it's hard to say how it has improved things. It's existed since I've been here. But it gives everybody the ability to see the physical implementations in a visual manner.

The solution is extremely critical to driving business change and transformation in our company because we do 100 percent of our data modeling using this tool. We meet with the business to show what exists and we show them what our changes are going to be to meet new requirements. We review that with business to get its agreement to the approach. We also meet with technology to show how it's going to be transformed in the physical implementation. So it is extremely critical to our everyday process.

The most valuable feature is the physical or visual representation of the database, showing the tables, the columns, the foreign keys, and the ability to generate DDL, so you can physically implement databases.

It lets you display the actual physically implemented databases or the logical databases. That enables you to review them with business users or technology people, to understand the relationships of the data throughout the company and show how data is joined together to achieve whatever the desired business results are.

I would like to see more support for working with the big-data world. There are so many new databases evolving and it's very hard for them to keep up with all of the new technologies. It would be good if they were able to dynamically support big-data platforms, other than Hive and Teradata. There's a new release coming out this year and they're adding two more platforms in that next release. So they are striving to keep up with technology, but technology is just evolving too rapidly. There are just too many options.

I've been using erwin since 1998 or 1999.

The solution is very stable. It continues to evolve. 

A lot of the things, a lot of the new tools that they're introducing as part of erwin, are to make it more of a data governance tool in general, beyond just the data modeling which we've traditionally used. That whole piece is rapidly evolving. I've been watching it evolve over the past two or three years. We're not ready to purchase the products yet that they're putting out because we feel things are still evolving, but in the next couple of years they'll be the leader in the entire data governance realm.

Data Modeler is very scalable. It keeps evolving as new technologies come out. People put in requests for it to be able to support different database platforms, and in just about every release in the past couple of years they've come out with support for one or two additional platforms. They are trying to keep up with customers' demands. They're very good about continuing to upgrade support for their legacy stuff as well. They're evolving and they're doing a pretty good job.

The product was sold by a company called Platinum when I first started using it. It was then sold to CA and I was involved when CA produced its first rollout. After being owned by CA, it then was spun off to its own, standalone company, as erwin. I was there for the initial deployment of that as well. So, I've done many deployments of erwin, as different releases have come out.

The setup has become more complex. That's probably related to the fact that they're doing more things on the cloud, such as licensing, which has caused problems because we have very tight security here. Access to servers outside of our firewall causes issues for people who work in certain regions around the world because we restrict access to the cloud for governance purposes. So, we have had some issues with licensing. People can't connect to the license server, because it's done over the cloud, so they have to do an off-line license, which locks the license. We have concurrent licenses. So when a license is locked, even though the person is no longer using the product, because that person is not connected through the cloud, erwin's system doesn't know to release the license. We've worked with erwin and they have tried to help mitigate that, but we still do encounter issues with licensing.

In terms of deployment, just the install of the product on somebody's machine takes about 10 minutes. It's not very long at all. There are other features, such as setting up users in Model Mart, which take longer because you have to analyze the user's needs and set up appropriate permissions. That could take longer, depending on what the user's roles are.

As for our implementation strategy for Data Modeler, we just deployed it on someone's computer. We tested it on that person's box, one that everybody had access to. We all got to try the tool to see that we wanted to use it and to understand its features. Once everybody was comfortable with the features of it, we then had to upgrade our Model Mart repository, which is where we store all of the erwin models. Everyone has to be on the same release. So, we have to QA the whole process of upgrading our Windows Server and upgrading our database server. After we do those upgrades, we can then deploy the software on the machines. 

That's probably one of the biggest issues: Everybody has to be on the exact same version and release to be able to work together, if you're using the Model Mart repository. It's not very backward-compatible.

We did have to involve erwin consultants because of the firewall issues that we were having when we were doing testing. We had to involve their helpdesk. Their helpdesk is extremely responsive. They actually tried to help us immediately on the phone. We needed a higher level of support so they scheduled meetings where we were sharing screens with them and they were able to help us. They were very helpful. One of the best features of erwin is its helpdesk.

It's hard to know how to gauge ROI. We've been using it since I got here. With the tool, we have a very good service-oriented architecture. We know exactly where all the data is; it's very clearly documented. If we didn't have this tool, I don't know how we would manage knowing where data is or manage having a consistent business glossary or data dictionary.

We've experimented with other solutions, such as ER/Studio, which has had different names. We experimented with SAP PowerDesigner, but that was not as robust in performing what we wanted it to do.

The main differences between the products we evaluated and erwin would be the ease of use, between logical and physical transformed models. The logical is more on the business side, and the physical is more on the technical side. The ease of maintaining those two models together was the number-one advantage of erwin. Number-two is the ability of the tool to support many platforms while successfully creating DDL, without issues with the DDL. erwin also has the ability to do compares of the models against the database, and to synchronize differences, whether importing database changes into the model or exporting the model to the database. Those were the primary things that it did well.

But I come back to ease of use. It's a very easy tool to train somebody on and for them to use. ER/Studio is probably the second-best product, but it's not as self-explanatory, it's not as easy to use. It's a little bit more clunky. It probably performs just as well, but it's a bit more difficult to use.

If you want good data architecture in your company, you need to have database design done. It's probably the most important factor for having things clearly modeled and documented. erwin Data Modeler is not just a modeling tool, it's also used for documentation. If you're using the tool's functions properly, analyzing the documentation, flagging fields that are NPPI data, it is invaluable for business use. You can generate data dictionaries, you can make sure people are speaking common languages, and you can enforce company standards so that people are doing things in a consistent manner. It's an invaluable tool. If you want to have good data architecture, you need to have a tool like this.

We don't currently use the collaborative web modeling capability. We just recently purchased that tool and we are planning on deploying it at the end of Q1 of this year.

We don't use the erwin data transformation for integration to a wider ecosystem. We are actually able to directly do all of the transformations that we need from erwin, so we're not required to do any transformations. It supports legacy systems like Db2, Oracle, SQL Server, and now Teradata and Hive, which were introduced in the past few years. But it can currently support all of the data modeling we need to support, so no transformations are needed.

We have different flavors of people who use the tool. We have people who are dedicated data architects, that's their full-time job. There are 15 to 20 of them in the company. And we have many people who do use it for very specific applications on more of a part-time basis, where they're doing the data modeling and reviewing it with an enterprise architect. There are about 150 people who are doing that. Overall, we have about 170 people who have access to the software.

For deployment, upgrades, and maintenance of the solution, we generally require four people. We require somebody to do a Windows upgrade; we require somebody to do a database upgrade, and that's for the Mart repository portion; and we have two people who do the testing for the erwin tool: somebody who installs the upgrades of erwin on the local machines, and somebody who's testing it. When it comes to the installs and the upgrades, each person who's using the tool is expected to do that on their own. We set up a deployment package and everyone runs it when they're told to execute the upgrade.

I use the solution for entity relationship data modeling to build the databases.

Drag-and-drop data modeling and reverse engineering out of databases are the most valuable features of erwin Data Modeler by Quest.

I would like the solution to be less rigid in terms of its theory. It supports the theory very well, but it's too rigid. It's focused on database design and theoretic database design. I'd like it to be able to do better extractions.

I have worked with erwin Data Modeler by Quest for 20 years.

The solution is too rigid in terms of usability. The other thing is you can do things to make it crash, and when it crashes, the models created with it become read-only. To be honest, I prefer using Visual Paradigm.

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

It took some coordination to get the license transferred to me. Otherwise, the solution's initial setup is straightforward.

I've probably spent half a day not running the installation but waiting for emails back from the vendor.

It's a good enough solution if the whole purpose of your data modeling is to generate databases. I also use data modeling for other purposes, and that's why I prefer Visual Paradigm. It allows me to do data modeling that's not so much focused on databases.

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

We usually use it to design new databases as well as reverse engineer some databases from third-party products, e.g., ERPs or monetary software.

The most valuable features are the ability to reverse engineer and do model comparison. With the reverse engineering, I can understand the databases from third-party products. With the model comparison, I can track the differences between two versions of the same database.

Because I can graphically see the Modeler database, that is very helpful for my job as it helps me understand the database. It is very different from SQL and DML scripts, which are very hard to understand with just sentences. When we have a graphic, that is very helpful. We can save time understanding that database.

I like the synchronization ability a lot because it can tell me to apply some level of governance to my models. I can be sure that the model in my documentation or development environment matches with the database that is working in our production environment. It is accurate. Though, it is not always fast when we have dozens of tables, but it works. I wait about an hour in order to have a big database synchronized.

The solution’s code generation ensures accurate engineering of data sources. It avoids rework.

I would like to have more data sources from other, different vendors. In recent years, the vendor has reduced the number of data sources, and I would like to have more data sources for every brand. For example, with Oracle, I would like to have compatibility for many versions, including old ones, not just the most recent. 

The technical support could be better. They could give faster solutions.

I have been using this solution since 1995.

It is stable.

Only when the database is too big, then we could have some trouble. We are talking about maybe 12,000 tables, then it starts to have some problems.

With erwin, we just need to add memory to the computer in order to work with bigger databases. However, it would be good to have erwin for other platforms, e.g., Linux and Macintosh, not just Windows. 

The technical support is good. They are highly skilled. 

Before erwin, I was manually using Notebook for my databases. Before erwin, I was designing databases and analyzing them manually all the time.

We chose erwin because it was the only solution which could help us design a database on the computer.

It saves a lot of development time. I think we are saving from two weeks to one month annually. It depends on the size and complexity of the database.

The solution’s automation of reusable design rules and standards is good compared to basic drawing tools. It saves time and keeps us from errors, which are very costly in the database. Therefore, we can get back our money very quickly.

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources makes the cost of the tool worth it.

erwin is expensive compared to other solutions. We are paying almost $6,000 per seat a month.

I have used different solutions along the way, but then I moved back to erwin. Besides erwin, I have tried IDERA Embarcadero, but I think erwin is more usable and has helped me to do my job better.

I rate this solution as nine out of 10.

We used this solution for three to five projects that we had.

They have a lot of features and the most up-to-date technology integration, which I haven't seen in other products.

In terms of features, I believe they were doing very well in the latest technologies as well.

There are too many features. People find it extremely difficult to navigate. It's a great product, but there are too many features and no one knows exactly where things are. For example, the documentation is not always straightforward, which is why I use another competitor's product, which is simpler and easier to use. It has more features than the product I previously used.

This is a very complex product.

They have a lot of features, and that may be the reason why I'm not familiar with them and has made it more complicated for me. 

In comparison to other products I've used, such as ER studio, which is a competitor to erwin. It is simple and easy to code as well as other functions. Even the coding has become much simpler. I can see that this is a little more complicated. I'm not certain. Right now, I can explicitly state that no features are required because I still need to explore some areas. Maybe the reporting area will be interesting if it is more dynamic.

I have been working with erwin Data Modeler (DM) for approximately four years.

We are using version 9 or 9.1.

Pricing is very high compared to any other product.

I would rate erwin Data Modeler (DM) a nine out of ten.