erwin Data Modeler by Quest Reviews

We use the Workgroup Edition for sharing data models across the organization. The primary reason we're using the Workgroup Edition over the Standard Edition is the centralized repository of models.

Standard Edition requires individuals to determine how to share data models, whether you share them in a local LAN directory, through email, SharePoint, or Livelink. You have to come up with your own versioning scheme and your method for sharing models. With the Workgroup Edition, because it has the centralized repository with version control embedded in it, it standardizes how your organization does versioning and centralizes all the models at the same time.

The solution's ability to compare and synchronize data sources with data models is fantastic. We use it for that on a regular basis to make sure that changes haven't been made to the database outside of the modeling process. I can take existing databases and reverse engineer them and understand their structure within 15 minutes. If I didn't have Data Modeler it would take hours. It increases our productivity and helps in understanding our legacy application.

The organization that I'm currently with has not historically done data modeling as a discipline. We're using the tool to introduce data modeling into the organization because it is an intuitive tool. There are other modeling products on the market that aren't as intuitive, tools that are currently in use at my company. With this tool, we have an easier ramp-up with our new staff because it is more intuitive.

The solution's support for Snowflake affects our organization's data modeling tremendously because we didn't have a decent tool for the Snowflake product. There are a couple of tools on the market, but they are not good modeling tools. The fact that erwin Data Modeler supports Snowflake is a huge benefit to this organization. The existing procedures couldn't be satisfied with the tooling that my company was using. It's a huge plus because it was difficult for teams that are migrating to Snowflake to adhere to the internal company standards of data modeling, because there were no products that offered Snowflake as one of the solutions.

It also reduces development time because you don't have to write DDL manually anymore. You use the data modeling tool to generate the DDL. It reduces development time by about 10 percent. Workgroup's code generation helps to ensure accurate engineering of data sources, which reduces the number of errors during development. If someone is writing DDL by hand and they don't get the syntax right, they have to figure out what's wrong with it to be able to fix it. It helps you build your table structures more quickly so that you can actually begin development of the business logic in your application layer.

The most valuable features of the Workgroup Edition are the

• centralization of the models
• flexibility of the directory structure
• application of the naming standards across all models in the repository.

The centralization of models helps share models across the organization. Instead of having to email someone and say, "Hey, where did you put the model for this?" it's easily found. It also makes it easy to organize models. When you work in a large organization that has more than 1,000 models, you need to be able to organize them in some fashion.

Historically, the Workgroup Edition had a flat structure so you had to name a model in a particular way to be able to find it, when you had thousands of models. With the current version, because you have a flexible directory, you can organize your models any way that your organization feels would work well.

In addition, the visualization side of erwin really helps people to understand the structure of their data. It greatly enhances their ability to create the appropriate modifications to their existing structure, because they can graphically see how their structure is currently laid out. It helps with maintenance on existing applications, and it dramatically helps, when you're doing greenfield, in understanding your data requirements in a graphical format. The graphical aspect helps non-technical people to understand the database design. For the non-technical folk, it is very helpful for understanding the design and whether or not the design is meeting their requirements.

For anyone who's interested in the data design of an application, or a warehouse, the erwin Data Modeling tool is very helpful. That's especially true for people who don't understand the structure of databases. It helps them understand the relationships between tables, and what is contained within a table. It's an understanding that they don't have without this kind of product.

I would like to see the ability to support more NoSQL platforms more quickly. 

In addition, enhancing the graphics to render more quickly would be beneficial for any user.

I've been using erwin Data Modeler since 1992. In my current company, they were already using Data Modeler when I started in December of 2020, but I'm implementing the Workgroup Edition. They didn't have that.

Workgroup is a really stable product. 

The challenges I have found with it, from a stability perspective, are simply because of the sizes of the organizations that I have worked at. The sizes of some of the warehouses we have are quite ridiculous. When you get upwards of 5,000 tables and a million columns in a single model, the tool shows symptoms, primarily, of memory issues, and it becomes slower. To be frank, it's a result of poor design of a legacy database in the first place. It's not a fault with the erwin product, rather it's the fault of the people who designed that database.

In the past, we have had problems with scalability, but the vendor has fixed all of those issues over the last two years. I contacted them directly and they fixed things in the product for all of their clients.

Their tech support is adequate. It's easy to elevate an issue if I run into support personnel who aren't capable of handling it.

The company that I'm with now uses IBM InfoSphere Data Architect. We're switching to erwin because the IBM product is inferior and it is in maintenance mode and will not be supported. It also does not support Snowflake or any non-relational databases, such as Cassandra or Couchbase or Mongo. Workgroup does.

The initial setup of Workgroup is easy. The installation software is very straightforward.

You make the rest of it as difficult as your organization needs it to be. The directory structure that you establish is dependent on what your organization requires. In addition, it offers two different methods of user-authentication and four different profiles to manage the security of who can do what within the centralized repository. It gives you complete flexibility for your data modeling practice to be as open or as closed as your organization desires.

The amount of time the deployment will take will be dependent upon the specifics of an organization's modeling. In a large organization, you can't just install software. You have to go through a process that takes weeks, such as packaging the software for distribution onto desktop. The back end of the Workgroup Edition, which provides you the centralized repository, is an easy implementation. It's the directory structure, and the security that you want as an organization, that drive complexity into the deployment. If I wanted to let every person in the organization modify every model, I could be done in a day. If I need 20 different Active Directory groups and different levels of security, then I have to think through how I want my organization to use the tool, to set up the security appropriately. The tool itself makes it very easy to do that. The hard part is deciding how you want your organization to operate.

We work directly with erwin.

I don't think we'll have any return on investment in the near term. It's more of a long-term investment and a change in the culture of the company. It will take time before it shows any ROI.

The tool is definitely worth its price.

We looked at ER/Studio. We chose erwin because ER/Studio does not support Snowflake or Cassandra or Couchbase. They do support Mongo, but that isn't a database that we use.

You really need to sit down and consider how you want to organize your models, and how you should set up security, based on your organization's needs. The bigger the company, the more complex it can be, so you really need to think that through prior to implementing.

The use cases are for our enterprise data warehouse where we have an enterprise model being maintained and we have about 11 business-capability models being maintained. Examples of business capabilities would be finance, human resources, supply-chain, sales and marketing, and procurement. We maintain business domain models in addition to the enterprise model.

We're on-premise, a virtualized data center. We're running this as client-server, the client being PC-driven and the back-end for the erwin Mart is virtualized Windows Servers.

Collaboration is very important because it's important to have an enterprise-view of data, as opposed to a project-specific view of data. Using the business capability models, we're able to augment those models based on a project-by-project implementation. And each of those implementations goes through a review process before those business capability models are finalized. That adds a lot of value in data consistency and data replication when it comes to the models. We can discover where there is duplication and inconsistency. It also helps with the data descriptions, the metadata, about the purpose of using certain designs and certain descriptions for tables and patterns, for the data elements. It helps enforce the data standards that we've adopted.

Each data modeler has their own way of designing the models, but no modeler is starting from a blank sheet of paper. By reverse-engineering models, and by creating models that are based off of popular packages — for example SAP or JD Edwards or Workday — you're able to construct your own data model and leverage the metadata that comes along with the application models. You are able to integrate the data based on these models.

These modeling tasks deal with applications, and some of the applications are mission-critical and some are not. Most of the applications are not; it's more an analytical/reporting nature that these models represent. The models are key for data discovery of where things are, which makes it more transparent to the user.

The solution's code generation pretty much ensures accurate engineering of data sources. If you're reverse-engineering a data source, it's good to have the script for examination, but it's valuable in that it describes data elements. So you get accurate data types from those. It cuts down on the integration development time. The mapping process of source-to-target is a lot easier once you know what the source model is and what your target mapping is.

The most valuable features are being able to visualize the data in the diagrams and transform those diagrams into physical database deployments. These features help, specifically, to integrate the data. When the source data is accumulated and modeled, the target model is in erwin and it helps resolve the data integration patterns that are required to map the data to accommodate a model.

Also, collaboration around maintenance and usage is associated with data model development and expertise coming from a review process, before the data is actually deployed on a platform. So the data models are reviewed and the data sources are discovered and profiled, allowing them to be mapped to the business capability models.

The modeling product itself is far and above anything else that I've seen on the market. There are certain inconsistencies when it comes to keeping up with other platforms' databases in the reverse-engineering process. It should also support more database platforms.

There should also be improvements to capture erwin models in third-party products, for example, data catalogs and things of that nature, where the vendors have to be more aware of the different releases of product and what they support during that type of interaction. Instead of being three or four releases behind from one product to another, the products should become more aligned with each other. So if you're using an Erwin model in a data catalog, you should be able to scan that model based on the level of the Erwin model. If the old model is a certain release, the capture of that should be at the same release.

I've been using erwin Data Modeler since 2014.

There haven't been too many problems with stability so we're pretty pleased with the stability of it. Once in a while things may go awry but then we open up a request.

We haven't had any issues with scalability. Licensing is very supportive of the scalability because of the type of license we use, which is concurrent. We don't anticipate any issues with scalability: not in terms of the number of users and not in terms of the scalability of some of the models. 

Some of the models are quite large and therefore our data modeling framework helps us because we're able to have multiple models that are loosely coupled and make up our enterprise model. So we're not maintaining one model for all the changes. We're maintaining several models, which makes it a lot easier to distribute the scalability of those models and the number of objects in those models.

Technical support has been pretty good. We've had licensing issues. There have also been some bugs that have been repaired and there have been some issues with installation. But all in all, it's been pretty good.

We did not have a previous solution.

The initial setup was pretty straightforward. 

The only thing that we would like to see improved would be having the product support a silent install. If we were able to deploy the product from a predefined script, as opposed to a native installation, such as on a Windows platform, that would help. We are such a large company that we would prefer to package the erwin installation in one of our custom scripts so we could put it in our application store. It's much along the lines of thinking of an iPhone or an Android application in an application store where you're able to have it scripted for deployment, as opposed to installing it natively.

Our deployment took just a few months. We constantly go through deployments as new people come onboard, especially consultants. Usually, with a consultant engagement using a data modeler, you have to be able to deploy the software to them. Anything that helps them out in that process is good.

Our deployment plan was to test the product in a development environment, and have people trained through either self-service video instruction or through on-the-job-training. We were then able to be productive in a production environment.

ROI is hard to measure. If we did measure it, it would be more of a productivity jump of around 10 percent and would also be seen in data standardization. All of these numbers are intangible. There is more of an intangible benefit than a tangible benefit. It's hard to really put a dollar on some of the data governance processes that erwin supports.

Standardization is very difficult to put a price tag on or to estimate its return on investment. But we do have data standards; we are using standard names and abbreviations and we do have some standards domains and data types. Those things, in themselves, have contributed to consistency, but I don't know how you measure the consistency. When it comes to enterprise-data warehousing, it's a lot easier for end-users to understand the context of data by having these standards in place. That way, the people who use the data know what they're looking at and where it is. If they need to look at how it's designed, then they can get into the product a little deeper and are able to visualize the designs of some of this data.

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources absolutely make the cost of the tool worth it. erwin supports the Agile methodology, which tends to stabilize your data before you start your sprints and before application development runs its course.

We pay on a one-year subscription basis.

The biggest lesson that I've learned in using this solution is to have a data governance process in place that allows you to use erwin more easily, as opposed to it being optional. There are times when people like to do design without erwin, but that design is not architected. It pays to have some sort of model governance or data governance process in place, so models can be inspected and approved and deployed on database platforms.

We use it primarily for first drafts of database scripts, both in a relational database environment and other types of environments. The models represent those physical implementations. The database scripting part is heavily modified after the first draft to include additional features of those database platforms. So we find erwin DM less valuable through that and we find it more valuable creating initial drafts and reverse-engineering databases. It cuts development time for us to some degree, maybe 10 percent, but all in all, there are still a lot of extensions to the scripting language that are not included with the erwin product.

In our company, there are about 130 users, globally. From time to time the number varies. Most of those users are either the data modelers or data architects. There are fewer enterprise data architects. The other users would just be erwin Web Portal users who want to have a little bit of an understanding about what's in a data model and be able to search for things in the data model. For deployment and maintenance of this solution we have about two infrastructure people, in an 8 x 5 support model.

The easiest way of exposing or sharing the model to all the users at the enterprise level is the feature I found to be valuable in the solution.

They should merge all those products because apart from the Mark Server, they have the Web Portal, which requires a separate installation and license. And it's not easy to maintain, but very easy to use. So you need additional resources such as memory, unlike if they merge those Web Portal and Mark Server, which would be a great solution.

I think they should be more open to or ready to be agnostic to any databases, such as MongoDB. Any database available in the market should be ready in their drivers because I don't think they can be ready. So all the popular databases like Oracle, MySQL, Microsoft, and SQL Server, but I haven't seen any connector in Cosmos DB SQL, so it should be in the big data or cloud solution.

I have been using erwin Data Modeler for a year.

It is not a very stable solution. I rate the stability five out of ten.

It is a scalable solution. Around 20 users are using the solution presently. I rate the scalability an eight out of ten.

The technical support team is fine.

Previously, we used SAP PowerDesigner. One of the primary reasons we switched to Data Modeler is that we need to expose our models so that the user can access them very efficiently and time-bound. If I develop a model and if it's a room, I can easily push that model into a web portal. The users can study and use it from there, unlike in the previous SAP PowerDesigner. You need to export an image or picture file or JPEG or PNG; then you have to share on SharePoint and upload it in Confluence of this. That is a very tedious way of sharing the model. The stability of the solution needs improvement.

The initial setup is straightforward. The solution is deployed through the desktop version available for Data Artifacts. There is also a repository, the data node, and a web portal which is the application or web application for data analysis and other users interested in starting the model. I did all the deployment.

The pricing of the solution is cheap. I rate the pricing a five out of ten.

SAP solution is more stable compared to Data Modeler and fits our requirements as an enterprise team.

I rate the overall solution a seven out of ten.

We use the erwin Data Modeler tool to document conceptual, logical, and physical data design. Business data models capture the understanding of the data from a business perspective, which can then drive physical design to ensure data is represented and used correctly.

The automated generation of the DDL ensures that the data store looks exactly as the data design. It also ensures that the standards that are governed are followed and implemented successfully.

We use the diagrams and data dictionary capabilities to help users understand the data environments, as well as how the data relates to each other. We'll use the naming standard master file to govern and ensure that we have consistent naming and abbreviations across and within data stores. We use the forward engineering templates to standardize and govern the generation of the data definition language that is used to actually make the changes to the data stores. We also use the Compare capability to ensure that we have up to date production data models. And we are looking forward to the integration of the Data Modeler metadata with the data intelligence suite in R2.

The visual data models for helping to overcome data source complexity and enabling understanding and collaboration around maintenance and usage are excellent. A picture speaks 1,000 words. Seeing a picture that shows you how the data relates to each other helps you better understand what the data is and how to use it. Pairing that information with a dictionary, which has the definitions of the tables, columns, the entities, and attributes, ensures that the users understand what the data is so that they can use it best and most successfully.

Its ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync is excellent. 

We don't typically use the configurable workspace and modeling canvas because while the platform allows for the flexibility to dynamically include multiple colors and multiple themes, feedback from business users is that the multiple colors and themes can become overwhelming. When you do that, you need to include a key so that people understand what the colors mean.

Its ability to generate database code from a model for a wide array of data sources cuts our development time. By how much depends on the number of changes that are required within the data store. It is certainly better to automate the forward engineering of the DDL creation, rather than having someone manually type it all out and then possibly make a human error with spelling irregularities.

Its code generation ensures accurate engineering of data sources. It decreases development time because it's automated.

I would like to see the reporting capabilities be more dynamic and more inclusive of information. The API is very sparsely understood by people across the user community.

I would also like to see a greater amount of integration with the erwin Data Intelligence Suite and the erwin Web Portal for the diagram delivery. That would be beneficial to all.

I have been using erwin for twenty years. 

It's very stable, especially having been available for use for so many years.

It is scaling well to include the new data structures, rather than being stagnant and only continuing to support the older DBMS types.

We have over 100 Data Modelers in my company and the users of the metadata go into the 1,000s.

We have an administrator who is responsible for the software upgrades, we have a governance community in the Center of Excellence, and we have the actual Data Modelers themselves who provide the delivery of the physical data models. We have data architects who create business, conceptual, and logical data models. And then, of course, we have our developers who use the data model information to understand the code that they are writing. We also have the business users who use the diagrams and the data dictionaries to understand the data so that they use it correctly.

Data Modeler is being used very extensively. We are considered power users within the community of users.

As new applications are developed, we may or may not need new licenses for erwin Data Modeler.

I have used SILVERRUN, which is a very old tool and actually has Sunset. I have also used SAP Sybase PowerDesigner. The primary reason for using PowerDesigner over erwin Data Modeler for that decision was that we were able to program the PL/SQL right into Sybase PowerDesigner. At the time, it had the capability to order the run of the PL/SQL. So the Sybase PowerDesigner would not make the changes to the database via the DDL, but it also generated the PL/SQL code that moved the data from source to target. That's a capability that erwin Data Modeler has never had. I don't know if it is on the roadmap for inclusion in the future, but I also do not see it as a requirement for erwin Data Modeler going forward because there are many ETL tools out there readily available.

I've also used IDERA. The interesting feature about IDERA that differentiates it from erwin Data Modeler is that the model repository actually separates the logical data models from the physical data models. Whereas erwin is basically the flip of a switch. It's not a true logical model, it's a logical representation of the physical data model.

I think the other thing that sets erwin Data Modeler apart is the model Mart repository, which protects a company's intellectual property within the data models and makes them available across the company so that the information is shared with anyone who has an erwin Data Modeler license. That was not available in SILVERRUN. It was also not available when I used PowerDesigner at the time. It was about 15 years ago for PowerDesigner. It is available for IDERA.

I find the setup straightforward. It is very easy to install. It took minutes.

We have seen ROI.

The reusability of some of the information within erwin Data Modeler, coupled with the capability to govern the information such as the data domains, the naming standard master file, degeneration of the DDL, every piece of automation ensures that there is consistency across and within data stores, and reduces the time to deliver the information because of the automation and governance built into the tool.

Whether or not the accuracy and speed of the solution and transforming complex designs into well-aligned data sources make the cost of the tool worth it would be a judgment call. I do think it is worth it. But of course, in this day and age where people are offshoring all of their work trying to save money, makes one consider the cost of any investment.

I think that the pricing is reasonable. It has called Concurrent licensing, where you can have a number of people share an erwin license. I think that that pricing is a little bit high, but that is a personal opinion.

The biggest lesson that I've learned is actually with a lack of data modeling. We have teams who have complained that data modeling takes too long. They would rather have developers manually code the DDL, which creates a lot of mistakes, increases the backlog, and increases not only the time to delivery but the cost to delivery. There is a lack of understanding of the agile methodology around data modeling and the incorporation of the emergent design happening in the scrum teams with the intentional design of the data architect creating a data model. Given an opportunity to follow the correct path and perform data modeling, we have seen a significant return on investment with decreases in delivery time and decreases in project cost.

I would rate erwin Data Modeler a ten out of ten. 

We use the solution for data modeling.

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

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

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

I have been using the solution for four months.

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

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

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

Neutral

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

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

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

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

In one of the companies, we used it as an information tool. We created a logical model so that the business would know what was in the offices down to the warehouse. The current use case is also the same. We have some places for information, so we can do a logical data model for them, but, usually, it would go towards building an actual database, which also involves reverse engineering of an existing one because people don't know what's in there.

It is currently on-prem, but we still have a separate server.

We want to bring different erwin components together and tell a business user story. So, having all of it on one platform to be able to tell one story makes it not as fragmented as components have been in the past. 

In my previous company, when we had 1,000 tables, 6,000 columns, and 14 subject areas, trying to explain to people in the organization was difficult. Without the tool, it would have been impossible. With the tool, it was a lot easier because you could show a steward how this is his or her domain. For each steward, you could say, "Well, this is your domain over here." Once they had that, they could understand what you were talking about. So, it improved communication. We had a point where two stewards were looking at the models, and one of them said, "I think that one that you've got over there is actually mine." The other one said, "I think you're right." So, we actually moved an entity from one subject area to another because now they had the ability to see what was in their subject area. They could go and see what wasn't theirs and should be someone else's. If we didn't have the tool, we wouldn't have that visibility and wouldn't have been able to recognize that sort of situation. 

Its ability to generate database code from a model for a wide array of data sources cuts development time. You don't have to re-key things. You put in the information at one spot, and it flows out from there. There are so many parameters you can put on the physical side. You can put in your indexes, and you can put in expected size changes. You can store all sorts of information within the model itself. It is a really good repository of all that sort of information, and then you just push a button, and it generates the other end. It works really well. In terms of time-saving, if you had to write it all out by hand, it would take weeks. It would probably take three or four times longer without the tool.

It certainly improves accuracy for the generation of target databases because you're only putting information in one spot. You don't have to retype it. For example, I saw the word conceptual model misspelled today. So, if you have to re-key something, no matter how careful you are, you're going to misspell things, which would cause problems down the track, whereas if you make a mistake in DM, there is only one place you have to go and fix it, and then, you would regenerate the downstream stuff. This means that you don't have to touch anything physical. You generate it, and then you can use it.

Being able to point it to a database and then pull the metadata is a valuable feature. Another valuable feature is being able to rearrange the model so that we can display it to users. We are able to divide the information into subject areas, and we can divide the data landscape into smaller chunks, which makes it easier to understand. If you had 14 subject areas, 1,000 entities, and 6,000 columns, you can't quite understand it all at once. So, being able to have the same underlying model but only display portions of it at a time is extremely useful.

I am currently trying to compare and synchronize data sources with data models, and it is pretty good. It shows you all the differences between the two systems. After that, it is a matter of what you want to do with them. It is certainly helpful for bringing models in and being able to compare. At the moment, I'm comparing something that's in a database with something that was in the DDL statement. So, these are two different sets of sources, and I can bring different sources together and compare them in the one, which is really helpful.

I still use Visio for conceptual modeling, and that's mainly because it is easier to change things, and you can relax some of the rules. DM's eventual target is a database, which means you actually have to dot all the Is and cross all the Ts, but in a conceptual model, you don't often know what you're working with. So, that's probably a constraint with erwin.

They have made it a lot easier, and they've done a lot, but there is probably still room for improvement in terms of the ease of presentation back to the business. I'm comparing it with something like Visio where you can change colors on a box, change the text color and that sort of stuff, and change the lines. Such things are a whole lot easier in Visio, but once you get a theme organized in erwin, you can apply that theme to all of the objects. So, it becomes easier, but you do have to set up that theme. I think they've got three to four initial themes. There is a default theme, and then there are two or three others that you can pick from. So, having more color themes would help. In Visio, you have a series of themes where someone who knows about color has actually matched the colors to each other. So, if you use the colors in the theme, they will complement each other. So, erwin should provide a couple more themes.

They could perhaps think of having an entry-level product that is priced a bit lower. For extra features, the users can pay more.

I have been using it at least since 2003. I have used it at multiple organizations.

It has always been really stable in the different organizations that I've used it in. It has always been a pretty good product.

It works fine with the number of people who have been using the product. We're talking about 10 to 12 people, not thousands of people. I haven't ever been in an organization where thousands of people even needed to get to the product. Probably the biggest drawback in scalability is the cost per seat rather than the actual product. The product works fine.

Our current organization has probably about 5 to 10 people using it. We're a consultancy, so we're using it in various roles. So, a lot of it is to do with understanding. As consultants, we try to understand what a client has in the organization and what sort of data they have to make sure there is actually data in the system that can answer their business questions. So, that's the sort of thing we use it for. We can turn around and give them designs. We can show what it is, and then we can turn around and make it what it would be. It is used by analysts and developers. They are not developing software. They are probably developing the database, but then, people would develop software.

I've used it on all the projects I've been on so far. I've been with this company for a short time, and it has come into play for pretty much all of the projects that I've been on. We want to use it more extensively. We want to use the erwin suite. We've got the modeler, but we also want to use their BI tool. We would like to evolve and come up with a story that links all of them together.

We have only just got the BI suite installed. We're starting to play around with it and see what we can do with it. We're doing some training on it at the moment. In a previous company also, somebody from erwin came to show it to us, and it was reasonably new at that point. That was last year. It is a reasonably new product. So, getting them to talk to each other has also been fairly new. erwin has only done it in the last couple of years. 

I haven't had dealings with them, but the dealings I've had with erwin as a company have always been really good. So, I would rate them a nine or 10 out of 10.

I use Visio on the conceptual side. We've got Informatica, and I think it has got a modeling component in there. We try to get a range of products because we're doing consulting in various organizations, and they have got various tools. Usually, it depends on what a client has already installed. Sometimes, it also depends on their budget. Something like Informatica is usually at the top right end corner of the Gartner Quadrant, but it could also be overkill for smaller organizations because the benefit may not be there. So, a lot of time, it is horses for courses. You have to sort of tailor any solution to meet a client's needs.

I haven't ever really installed erwin. One of the other guys has done that. Most of the places had it installed already. Usually, the complexity depends on how the organization does its software deployment. So, you have to go and request the software and then somebody has to give you the package. Once you get the package, it is pretty straightforward. It is usually less of a problem on erwin's side and more of an issue with how an organization deploys any erwin software, but once you deploy it, it works fine.

Some places that I've worked with were very strict about doing testing on COTS products to make sure that there are no viruses on it and also to make sure that it plays nicely with the rest of the system. So, those sorts of organizations may take longer in terms of testing. You put it on a test machine first and make sure it is not going to kill anything. They might have to repackage some stuff before they put it out to the network. To deploy a vanilla thing, I would think that it would only take a couple of hours.

In terms of maintenance, at the moment, I think we've got one person. The main thing is deploying new versions. You've got a server stood up, and you have to put the software out there. I don't know if there is anything else beyond that.

We haven't done an ROI for the current version. When you look at the total cost of creating or understanding what you've currently got through reverse engineering, and you look at the total cost of creating new products and new databases and maintaining them over time, and then you put that into the return on investment model, it is well worth it.

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources make the cost of the tool worth it. If you didn't have the tool and a single developer or a single modeler was trying to do the same thing, the speed would be three or four times slower. If you multiply that by the cost of that person and then you also consider the cost of the other people who are waiting for that person to create a database design, it multiplies out. So, it is well worth it.

It has increased in price a fair amount over the years. It has always been expensive because it is a comprehensive product, and presumably, they have to do a tremendous amount of testing to make sure that everything works. It has always been dear because usually, a very specific target audience of data architects has the need for modelers, and not everyone in the organization would need to get a copy of it. Only people who are actually working in the database space need it. So, it has always been a very specialized piece of software, and it has been priced accordingly.

I don't specifically know what we're paying now. About three years ago, in another organization, I have this memory of 6,000 AUD a seat or something like that, but I am not sure. In the mid-2000s, it was something like 1,200 AUD a seat. I get the impression that there was a price jump when it was spun off from CA as a separate company, which is understandable, but it could sometimes be a barrier in some organizations picking it up.

I haven't talked to erwin people yet, but I'm going to suggest to them that they could perhaps think of having an entry-level product that is priced a bit lower, and then, you can buy the extra suite. That's what Microsoft does. They package a few things so that you have something, but if you want this extra stuff that has enterprise features, such as they talk to each other and have great bits and pieces, you have to pay more. I don't think there are any additional costs. It is per product, and there are different license levels. 

Oracle Data Modeler, which is free, is one of the competitors that erwin has. You can't argue with the price point on that one, but erwin is much more comprehensive and easier to use. It is easier to display information and models to business people than something like Oracle Data Modeler, which does the job, but erwin does it a lot better. So, my advice would be that if you can afford it, get it.

Its visual data models have certainly improved over time in terms of overcoming data source complexity and enabling understanding and collaboration around maintenance and usage. It was originally designed as a tool to build databases with, and it retains a lot of that. It still looks like that in a lot of cases, but it has also been made more business-friendly with a sort of new front end. So, it used to be all or nothing where when you wanted to show somebody just the entity names or just the entity descriptions, you had to switch all of the entities on your diagram just to show names. Now, you can show some of them. You can shrink down some of them, and you can keep some of them expanded. So, it has become a more useful information-sharing tool over time. It is extremely helpful.

In my previous company, it was the enterprise data model, and you could paper a room with it if you printed the information out. To present that information to people, we had to chunk it down into subject areas. We had to present smaller amounts of information. Because it was linked to the underlying system, we could reuse the information that we had in a model in other models. The biggest lesson was to chunk the information down and present it in a digestible form rather than trying to show the entire thing because otherwise, people would run away screaming.

One of the places didn't have a modeling tool in it, and they were trying to do the documentation using Confluence. It was just a nightmare trying to keep it maintained with different developers using different tables and then needing to throw something into one and adding something into another one. It was just a nightmare. If they had one tool where they could put it all in one place, it would have been so much easier than the mess they had.

I would rate erwin Data Modeler a nine out of 10.

We use erwin to design conceptual, logical, and physical data models for new projects. We use a Forward Engineering tool to forward engineer data models into new database structures. We use the reverse engineering tool to bring databases into data models and erwin. We also generate HTML reports of the models to share with our customers.

Whenever we do have a new project that requires a new approach, we do try using erwin for it. For example, if we have an XSD message file, then we would try to see if there is a way to get that into erwin for better visibility of the structures that we have to work with.

The product has helped us standardize our data modeling efforts across the enterprise in regards to visuals and naming. We also use the Mart Tool from erwin, which allows us to store our data models in a centralized repository, which gives everyone visibility on what is out there and how it is all related.

We discuss existing and new business requirements with business users, data architects, and application developers to figure out how to capture and visualize concepts in their relationships. One thing we do have standard in all of our models is that we use the information engineering notation. This is standard across our enterprise. We do use a diagram hierarchical layout to help visualize things, especially when we reverse engineer a database, as we want to have some sort of a clear visual layout of things.

We find a few of erwin tools most valuable:

• The Bulk Editor lets us easily make a lot of similar changes within our data model.
• We use the Forward and Reverse Engineering tools to help us speed things up and create things that would have to be done otherwise by hand. E.g., getting a database into a data model format or vice versa.
• The Report Designer is extremely useful because we can create reports to share with our business users and have a business discussion with them on how things work.

We find the text manipulation through the Bulk Editor to be extremely helpful. There were times where we had a set of entities which were not following our standards. With the help of the Bulk Editor, we were able to form those names with a few Excel formulas to follow our standards.

The Reverse Engineering functionality is good and easy to follow. It works really well. For the most part, we have been able to get any database to work with our data model format.

We quite heavily use the templates that exist to apply our standards to the data models created by our data modelers. We are able to use the templates to apply things like Naming Standards, casing on names, and colors to all our data models without having to be on top of it.

Complete Compare is not user-friendly. For example, the save known changes as snapshot does not work as expected. We are unable to find the exported files in our workstations at times. Complete Compare is set up only to compare properties that are of interest to us, but some of the differences cannot be brought over from one version of the model to another. This is despite the fact that we are clicking to bring objects from one place to another. Therefore, it's hard to tell at times if Complete Compare is working as intended without having to manually go into the details and check everything. If it could be redesigned to a degree where it is easier to use when we bring things over from one site to another and be sure that it's been done correctly, that would be nice to have. We would probably use the tool more often if the Complete Compare were easier to use.

The client performance could be improved. Currently, in some cases, when we delete entities it causes the program to crash. Similarly, for Mart's performance, we need to reindex the database indexes periodically. Otherwise browsing through the Mart, trying to open up or save a data model takes unusually long.

There are several bugs we discovered. If those were fixed, that would be a nice improvement. We encounter model corruption over time, and it is one of those things that happens. There is a fix that we run to repair this corruption by saving the model as an XML file or to the Complete Compare tool. If this process could somehow be automated, having erwin detect when a model is corrupted and do this process on its own, that would be helpful.

There are several Mart features that could be added. E.g., a way to automatically remove inactive sessions older than a specified date. This way we can focus on seeing which users have been utilizing our central repository recently, as opposed to seeing all of what happened since five years ago. This would be less of a problem if the mart administrator did not have trouble displaying all of the sessions.

On the client side, there are some features that would come in handy for us, e.g., Google Cloud Platform support or support for some of the other cloud databases.

If we had a better way to connect and reverse engineer the databases into data models, that would help us.

Alter scripts can be troublesome to work with at times. If they can be set up to work better, that would help. On the Forward Engineering side of things, by default, the alter syntax is not enabled when creating alter scripts. We strongly believe this is something that should be enabled by default.

On the Naming Standards (NSM) side of things, there is a way in erwin to translate logical names into physical names based on our business dictionary that we created. However, it would be nice if we could have more than one NSM entry with the same logical element name based on importance or usage. Also, if erwin could bring in the definitions as part of the NSM and into a model, then we could use those definitions on entities and attributes. That would be beneficial.

We have been using it for at least 15 years, a very long time.

Overall, the server is mostly stable. After we implemented the reindexing fix on our database, everything works pretty well. On the client side, it is mostly stable, but sometimes it's not. There are certain actions that cause the client to crash. This has been much less of the case since we switched to the 64-bit version of erwin, which has been a great improvement.

We have found erwin’s code generation ensures accurate engineering of data sources. We haven't seen any issues. We pass our code off to DBAs to implement. Therefore, the DDL that we generate gets passed up to the DBAs who will add some physical features and may add some performance indexes, then we will reverse engineer that information and have that in our data models.

For our bug related issues, we have been given the recommendation to upgrade to the latest version. We are in process of doing that and will see how that works out. We also submitted some other things through erwin's idea board. There are a few issues that we haven't reached out to erwin on yet.

Currently, we have a team of people who take turns helping out other users. They figure out how to do different things. If there is a server side issue, we do have several people as well who will look into that. In the past, we did manage a lot with one person. However, we realized it was quite an undertaking. You either need one fully dedicated person to look into this or several people to take turns.

We have a Windows Server and a SQL Server database. Therefore, we have SQL Server dedicated staff to help us with any SQL Server issues and Windows support staff who help us with any Windows issues. We don't generally have any issues with erwin. From a technical support side, we do have a support staff if we were to run into any issues. Our team of five data modelers are pretty well-experienced with both the tool, Mart, and any sort of communication issues that we might have to deal with, e.g., if the SQL server went down, then these folks would be the liaisons to the SQL Server team.

Given our mostly constant user base and constant growth of new data, our impressions of the scalability are great. Currently, we have about 2000 models in the Mart repository. Reaching this capacity has slowed down interactions with the Mart as opposed to when we had a fresh Mart. When we first started using the Mart server, it took about two seconds to open things like the Catalog Manager or Mart Open dialogue. Now, it takes around 10 seconds to do that part. For the most part, it seems to be pretty scalable. We've been able to continue using the tool given our large volume of models.

There are 35 to 40 users plus some occasional DBAs who use it to tweak any of the DDLs that they might want to pull.

We are able to develop our data models for mission-critical tasks with the solution’s configurable workspace and modeling canvas. We have 20 enterprise data modelers. We are mostly working on the standard RDBMSs: SQL Server, Db2, and Oracle. We also use some cloud technologies, like GCP, Azure, and Couchbase. Then, there are approximately another 15 data modelers which work exclusively in Oracle Business Intelligence from a data modeling aspect. This is for dimensional repository and data warehouse stuff. Therefore, we have about 35 to 40 data modelers in our organization for pretty much every major project that passes some sort of funding gate. Anything that is mission-critical for our organization will come through one of our two managers, depending on whether it's relational modeling or dimensional modeling. All of the database designs come through these two groups. There are some smaller database designs which we may not be involved with, but all of the critical application work comes through these teams. In regards to focusing on mission-critical tasks, we really wouldn't be able to do it without a tool like erwin. Since we are all very well-trained in erwin, it is the tool that we leverage to do this.

Erwin generates the DDL for all our projects. We rely on the tool for accuracy as some of our projects have hundreds of entities and tables.

When it is bug related, we get a bug fix or are told to upgrade to the latest version. This has worked out in the past. Where it is question related, we have been pretty happy with their Tier 1 support's responses. We will receive some sort of a solution or suggestion on how to proceed in a very timely manner.

We would like support for JSON reverse engineering. That is something which is completely missing, but is something we have been working with quite often recently. If erwin could support this, that would be incredible.

On the client side, the setup was mostly straightforward. It was a matter of going through the installer, reading a little bit, then proceeding to the next step. In the end, the installation was successful.

On the server side, it has been a bit more complex. We did have some documentation provided by erwin, but it wasn't fully intuitive nor step-by-step. Some things were missing. It was enough to get started, then figure things out along the way.

On the client side, it takes five to 15 minutes to do the installation or upgrade to a newer version. On the server side, from the moment we backed up everything on the server and disabled the old mart application, the upgrade took about two hours. If you include all the planning, testing, and giving support users enough time to do everything, the upgrade took about three months. In general, these are the timeframes we experienced through in the past.

We simply used the documentation provided by erwin. Between the few of us that worked on the upgrade at our company, we had enough of a technical background to be able to figure out things out on our own. There were five to 10 people who worked on this initially:

• We had one person who helped with the database side of things.
• We had another person do everything on the application server.
• To test out of the different features of erwin in the new version and ensure that the existing features worked as intended, we involved several additional people from our team.

We go through a pretty rigorous testing procedure when we bring in a new release of any software like this. Although it's not affecting customers directly, it certainly affects 35 to 40 people. Therefore, we want to ensure that we do not mess them up by not having something work. Normally, we go through this with any product. We first install it on a test environment and have a bunch of folks jump on. This is to ensure everything is working the way we want and work out all the kinks when setting up the production server before we move it into production.

It is an invaluable tool for us. It has been part of our data governance process in regards to database design for at least 15 years.

The amount of time saved is proportional to the amount of changes in the databases that we are implementing at any time. The more code we generate (because the model is bigger), that saves us more time because we don't have to write everything up manually and check to make sure that the code is correct. If we had to give a number, this saves us anywhere from minutes to hours of work. The time frame depends on the data modeler, as some data modelers generate more code than others. Therefore, it could be on a daily, weekly, or monthly basis and depends on the project. Some projects are in maintenance mode and not going through a lot of changes. It is way easier to use this solution because then we have a data model to reference for something that was developed approximately two months ago and somebody can just pick it up versus if someone had to generate changes to a database without a data modeling tool.

The tool certainly makes the data modeling staff more productive than if they did not have a similar tool. Without erwin, our jobs would be a lot more tedious and take a lot more time.

We evaluated IDERA two years ago and decided to stay with erwin mostly because the staff is mostly familiar and comfortable with the tool. We think that was the overriding factor. The other thing would be converting from erwin to IDERA would be a major undertaking that we just weren't prepared to do.

The fact that it can generate DDL is a major advantage over something like Visio, where you can also do a database diagram. We don't have a Visio version that would generate DDL, so I'm assuming it doesn't, and any tool that can generate code for database definition will certainly have an advantage over a product that doesn't.

I would certainly recommend this product to anyone else interested in trying it out. The support from the vendor is great. The tool overall performs well and is a good product to use.

Having a collaborative environment such as the one that erwin provides through the Mart is extremely beneficial. Even if multiple people aren't working on a single model, it's nice to have a centralized place to have all the models. It gives us visibility and a central place to keep everything in one place. Also, it supports versioning, which allows us to revisit it at different points in time to go back to in the model, which is really helpful.

We do not use erwin to make changes directly to the database.

We have no current plans to increase our usage of erwin other than adding more models.

We would rate the solution overall as an eight (out of 10).

Our primary use is for doing database designs on just about any platform. The main users are dedicated data architects, while we also have development team staff using the tools to review models. Additionally, our database admins access the solution for implementing the Data Definition Language (DDL).

The solution is excellent in providing a visual representation of a database and can generate DDL for implementing changes. We use DDL for logical purposes to review with business people, ensuring they have the required fields for processing. We also use it as a data dictionary for the physical data model to understand all the purposes of the terms. This helps us map the logical and physical terms with the business definition to understand our data.

Data Modeler is straightforward to use and fulfills all our requirements. 

Although Quest Software has made tremendous strides in recent years, they need to evolve more in the big data arena; erwin Data Modeler could use a little more work when it comes to big database designs.

We've been using the solution since the 90s. 

The product is very stable. 

The platform is highly scalable; we use it for our entire enterprise data architecture. 

The tech support is pretty good, but there's always room for improvement, so I rate them eight out of ten.

Positive

Our initial setup was over 20 years ago, but I know it to be almost effortless; it's a basic software installation that takes about five minutes.

Regarding maintenance, there are occasionally new versions and releases, and we have dedicated data architect teams that coordinate so every team upgrades simultaneously.

We've continued to use the product for many years and compared it with others on the market. The pricing is reasonable considering what the solution offers and what we pay. There are cheaper tools, but they may not be as robust and easy to use, so it's worth the money.

I rate the solution nine out of ten.

My advice to those considering the solution is to use dedicated data architects; when you give this type of product to development teams, there can be issues around creating and following standards, which is essential for data model integration. You don't want different teams defining the same types of columns with varying lengths, like dollar amounts. If the entire company agrees that the dollar amount field is 18 digits long and two digits to the right of the decimal place, then you're consistent. If different teams disagree, data can't be transferred from one database to another without truncation. Having a centralized team that enforces standards is critical.