erwin Data Modeler by Quest Reviews

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.

We use erwin Data Model to create logical and physical data models.

The solution has been very helpful. The logical and physical data models provide visualization for communication across the business, among the data team, and technical team. Without this solution, communication would be difficult.

The ease and quick ability to create the model is valuable. The fitting model is very intuitive. 

The other cool feature is the reverse engineer feature. If we connect to the database, we can reverse engineer from the database itself of the physical model. That gives us the relationship of the data if not much documentation is available.

So far, we have used it in either a workroom version or a standalone version. It does not have a cloud application.

We have licenses for Mac Linux since a lot of our people have Mac laptops, so erwin should work on their cloud application.

I have been using erwin Data Modeler since 2006. 

It is a stable solution. So far, we have not had many problems. Sometimes it freezes because it is a resource-hungry application, so it uses a lot of memory and a lot of processing power while running. But so far, we have not lost any of our work.

We had a concurrent license where multiple people could it. Typically, this is not a tool that you’ll use for hundreds of people. It’s very scalable for ta limited number of people.

The technical support team is pretty prompt. The tier-one support is pretty prompt. We contacted them a couple of times for a security patch and a few times for transferring the license to a different user. Their support was good.

Positive

I have tried Lucidchart, PCO, and ER Studio.

erwin and ER Studio are very comparable. I personally think both are more or less the same. However, erwin has richer features, and productivity is boosted. Once I have a model in mind, putting that in the tool is very quick, followed by generating the DDL, creating the table, and integrating it with the data explorer. The bulk editor feature is also very useful. 

The initial setup is straightforward for someone who understands the data.

For the workgroup version, you need to set up a database and then connect to the database. After installation, you have to maintain those connections. For someone who is well-converged with a database, it’s simple. If someone has not worked with web databases, they might find it a little complex. The deployment was done within a couple of hours by three to four people.

The deployment was done in-house.

There is either a one-year or three-year license. It is not a pay-as-you-go license like a SaaS solution. It’s more of a traditional licensing. They are a little bit on the pricier side.

However, there are tools that are less pricey, and some of them are open source and free as well.

From a pricing perspective, it is not very competitive in the current market.

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

They have small videos that explain how to use the tool and they are very useful. If you know the principles of data modeling, erwin will be very easy to learn. If you are new to data modeling, then I’d recommend getting a course on data modeling first.

We use it for our conceptual business-data model, for logical data modeling, and to generate physical database schemas. We also create dimensional modeling models.

One of the ways Data Modeler has benefited our company is that it gives us the ability to engage with the business alongside IT, because it's friendly. It has friendly views that we can use when we meet with them. They can follow them and understand them. That increases the quality and accuracy of our IT solutions.

The solution's ability to generate database code from a model for a wide array of data sources helps cut development time. We generate all the DDL for our hub through a modeling exercise and generate the alter statements and maintenance through the erwin modeling tool. I would estimate that reduces development time by 30 to 40 percent because it's so accurate. We don't have to go back in. It takes care of the naming standards and the data types. And because we use OData, we generate our service calls off of those schemas too. So that's also more accurate because it uses what we've created from the model all the way through to a service call with OData.

I find the logical data modeling very useful because we're building out a lot of our integration architecture. The logical is specific to my role, since I do conceptual/logical, but I partner with a team that does the physical. And we absolutely see value in the physical, because we deploy databases for some of those solutions.

I would rate erwin's visual data models very highly for helping to overcome data source complexity. We have divided our data into subject areas for the company, and we do a logical data model for every one of those subject areas. We work directly with business data stewards. Because the logical and the conceptual are so easy to look at, the business side can be very engaged and collaborate on those. That adds a lot of value because they're then governing the solutions that we implement in our architecture.

We definitely use the solution's ability to compare and synchronize data sources with data models. We have a data hub that we've built to integrate our data. We're able to look at the data model from the source system, the abstracted model we do for the hub, and we can use erwin to reverse-engineer a model and compare them. We also use these abilities for the lifecycle of the hub. If we make a change, we can run a comparison report and file it with the release notes.

I would like to see improved reporting and, potentially, dashboards built on top of that. Right now, it's a little manual. More automated reporting and dashboard views would help because currently you have to push things out to a spreadsheet, or to HTML, and there aren't many other options that I know of. I would like to be able to produce graphs and additional things right in the tool, instead of having to export the data somewhere else. And that should work in an intuitive way which doesn't require so much of my time or my exporting things to a spreadsheet to make the reporting work.

I've used the erwin Data Modeling tool since about 1990. I work more with the Standard Edition, 64-bit.

It's stable. This specific tool has been around a long time and it has matured. We don't encounter many defects and, when we do, a ticket is typically taken care of within a couple of days.

We're using standalone versions, so we don't need to scale much. In the Workgroup Edition we've got it on a server and we have concurrent licensing, and we've had no issues with performance. It can definitely handle multiple users when we need it to.

At any time we have six to 10 people using the Workgroup Edition. They are logical data modelers and DBAs.

We've already increased the number of people using it and we've likely topped-out for a while, but we did double it each year over the past three years. We added more licenses and more people during that time. It has probably evolved as far as it's going to for our company because we don't have more people in those roles. We've met our objectives in terms of how much we need.

I would rate erwin's technical support at seven out of 10. One of the reasons is that it's inconsistent. Sometimes we get responses quickly, and sometimes it takes a couple of days. But it's mostly good. It's online, so that's helpful. But we've had to follow up on tickets that we just weren't hearing a status on from them.

They publish good forums so you can see if somebody else is having a given problem and that's helpful. That way you know it's not just you.

We did not have a previous solution.

I've brought this tool into four different companies, when I came to each as a data architect. So I was always involved early on in establishing the tool and the usage guidelines. The setup process is pretty straightforward, and it has improved over the years.

To install or make updates takes an hour, maybe.

A lot of the implementation strategy for Data Modeler in my current company was the starting of a data governance and data architecture program. Three years ago, those concepts were brand-new to this company. We got the tool as part of the new program.

For deployment and maintenance of the solution we need one to two people. Once it's installed, it's very low maintenance.

We did it ourselves, because we have experience.

We're very happy with the return on investment. It has probably exceeded the expectations of some, just because the program is new and they hadn't seen tools before. So everyone is really happy with it.

erwin's automation of reusable design rules and standards, especially compared to those of basic drawing tools, has been part of our high ROI. We're using a tool that we keep building upon, and we are also able to report on it and generate code from it. So it has drastically improved what was a manual process for doing those same things. That's one of the main reasons we got it.

We pay maintenance on a yearly basis, and it's a low cost. There are no additional costs or transactional fees.

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

We looked at a couple of solutions. Embarcadero was one of them.

erwin can definitely handle more DBMSs and formats. It's not just SQL. It has a long list of interfaces with Oracle and SQL Server and XSD formats. That's a very rich set of interfaces. It also does both reverse- and forward-engineering well, through a physical and logical data model. And one of the other things is that it has dimensional modeling. We wanted to use it for our data warehouse and BI, and I don't believe Embarcadero had that capability at the time. Most tools don't have all of that, so erwin was more complete. erwin also has several choices for notation and we specifically wanted to use IDEF notation. erwin is very strong in that.

The con for erwin is the reporting, compared to other tools. The interface and reporting could be improved.

My advice would depend on how you're going to be using it. I would definitely advise that, at a minimum, you maintain logical and physical views of the data. That's one of the strengths of the tool. Also, while this might sound like a minor thing, it's important to create standard templates — Erwin is good at that — and you can customize them. You can create a standard template so that your models have the same look and feel. And then, anyone using the tool is using the same font and the same general layout. erwin's very good at helping enforce that. You should do that early on so that you don't have to redo anything later to make things look more cohesive.

Another feature of erwin is that it can help you enforce your naming standards. It has little modules that you can set up and, as you're building the data model, it's ensuring that they conform to the naming standards that you've developed. I think that's something that some people don't realize is there and don't take advantage of.

The biggest lesson I have learned from using this solution faces in two directions. One is the ability to engage the business to participate in the modeling. The second is that the forward-engineering and automation of the technical solution make it more seamless all the way through. We can meet with the business, we can model, and then we can generate a solution in a database, or a service, and this tool is our primary way for interacting with those roles, and producing the actual output. It's made things more seamless.

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 erwin DM as a data modeling tool. All projects in the data warehouse area go through the erwin model first and get reviewed and get approved. That's part of the project life cycle. And then we exude the scripts out of DM into Snowflake, which is our target database. Any changes that happen after that also go through erwin and we then make a master copy of the erwin model.

Our solution architecture for projects that involve erwin DM and Snowflake is an on-prem Data Modeler desktop version, and we have a SQL database behind it and that's where the models are stored. In terms of erwin Data Modeler, Snowflake is the only database we're using.

We are not utilizing a complete round-trip from DM for Snowflake. We are only doing one side of it. We are not doing reverse-engineering. We only go from the data model to the physical layer.

We use erwin Data Modeler for all enterprise data warehouse-related projects. It is very vital that the models should be up and running and available to the end-users for their reporting purposes. They need to be able to go through them and to understand what kinds of components and attributes are available. In addition, the kinds of relationships that are built in the data warehouse are visible through erwin DM. It is very important to keep everybody up to the mark and on the same page. We distribute erwin models to all the business users, our business analysts, as well as the developers. It's the first step for us. Before something gets approved we generally don't do any data work. What erwin DM does is critical for us.

erwin DM's support for Snowflake is very helpful from the data modeling perspective and, obviously, the JDBC and native connectivity also helps us in simplifying the push mechanism we have in erwin DM. 

Primarily, we use erwin for data modeling only, the functionality which is available to do logical models and the physical model. Those are the two areas which we use the most: we use a conceptual model first and the logical model, and then the physical model.

When we do the conceptual data model, we will look at the source and how the objects in the source interact, and that will give us a very clear understanding of how the data is set up in the source environment. The logical model gives developers, as well as the data modelers, an understanding of exactly how each object interacts with the others, whether a one-to-many, many-to-many, many-to-one, etc. The physical model, obviously, helps in executing the data model in Snowflake, on the physical layer.

Compatibility and support for cloud-based databases is very important in our environment because Snowflake is the only database to which we push our physical data structures. So any data modeling tool we use should be compatible with a cloud data warehouse, like Snowflake. It is definitely a very important functionality and feature for us.

We are planning to move, in 2021, into their server version, where multiple data modelers can work at the same time and share their models. It has become a pain point to merge the models from individual desktops and get them into a single data model, when multiple data modelers are working on a particular project. It becomes a nightmare for the senior data modeler to bring them together, especially when it comes to recreating them when you want to merge them. That's difficult. So we are looking at the version that will be a server-based model, where the data modelers can bring the data out, they can share, and they can merge their data models with existing data model on the server.

The version we're not using now—the server version—would definitely help us with the pain point when it comes to merging the models. When you have the desktop version, merging the models, two into one, requires more time. But when we go over to the server, the data models can automatically pull and push.

We will have to see what the scalability is like in that version.

Apart from that, the solution seems to be fine.

I've been using erwin DM for years, since the early 2000s and onwards. It's a very robust tool for data modeling purposes.

We have five to seven data modelers working on it at any moment in time. We have not seen any scalability issues, slowness, or that it is not supporting that level of use, because it's all desktop-based

When we go into the server model, where the web server is involved, we will have to see. And the dataset storage in the desktop model is also very limited, so I don't think going to the server model is going to impact scalability.

In our company, erwin DM is used only in the data warehouse area at this moment. I don't see any plans, from the management perspective, to extend it. It's mostly for ER diagrams and we will continue to use it in the same way. Depending on the usage, the number of concurrent users might go up a little bit.

I have interacted with erwin's technical support lately regarding the server version and they have been very proactive in answering those questions as well as following up with me. They ask if they have resolved the issue or if anything still needs to be done. I'm very happy with erwin's support.

The biggest lesson I have learned from using erwin DM, irrespective of whether it's for Snowflake or not, is that having the model upfront and getting it approved helps in reducing project go-live time. Everybody is on the same page: all the developers, how they interact, how they need to connect the various objects to generate their ETL processes. It also definitely helps business analysts and end-users to understand how to write their Tableau reports. If they want to know where the objects are, how they connect to each other, and whether they are a one-to-one or one-to-many relationship, etc., they can get it out of this solution. It's a very central piece of the development and the delivery process.

We use Talend as our ETL and BI vendor for workload. We don't combine it with erwin DM. Right now, each is used for its own specific need and purpose. erwin DM is mostly for our data modeling purposes, and Talend is for integration purposes.

Overall, erwin DM's support for Snowflake is very good. It's very stable and user-friendly and our data modelers live, day in and day out, on it. No complaints. There is nothing that impacts their performance.

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.

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

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

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

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

erwin Data Modeler by Quest is a stable solution.

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

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

The solution’s technical support is good.

Positive

I have previously used IDERA ER.

The solution’s initial setup is easy.

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

erwin Data Modeler by Quest is an expensive solution.

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

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

I would recommend the solution to other users.

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

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.