erwin Data Modeler vs. InetSoft Style Intelligence

I have had a chance to use few other data modeling tools from Quest and Oracle, but I am most comfortable using erwin Data Modeler. They understand your data modeling needs and have designed the software to give you a feeling of completeness when you are designing a data model.

Incentivized

It's great for the accumulation and assimilation of various data formats to be channeled into a single end-point, whether that be a table or a report. It reminds me so much of SPLUNK in that regard. The application is also very easy to use and has been configured in such a way that it is appealing and productive for both novice and expert users. I was able to pick up the basis after a solitary day's training. We've mainly used it to create bespoke dashboards and visuals, thereby allowing for effective report writing. This was a major consideration from Senior Management before the application was purchased. There haven't been any real drawbacks with the software thus far.

Incentivized

• Reverse Engineering: I love the way we can import an SQL file containing schema meta data and generate ER diagram out of it. This is specifically useful if you are implementing erwin Data Modeler for an existing database.
• Forward Engineering: We use this feature very frequently. Where we do database changes in our physical and logical data models and then generate deployment scripts for the changes made.
• Physical vs Logical Models: I like to have my database model split into physical and logical models and at the same time still linked to each other. Any changes you make to logical model or physical model shows up in the other.

Incentivized

• Easy to use with a very user-friendly interface, making onboarding with the tool a lot easier.
• Able to mash up/integrate data from different sources and file types which helps a lot with consolidation.
• Good customer service/support that makes solving problems/issues a lot faster.

Incentivized

• Cost is the single largest barrier to entry with this tool.
• Would like to see a greater variety of export options available for use outside of the tool, for example as a vector graphic.
• Support has been uneven at times.

Incentivized

• I think the user interface is in need of an upgrade, as its starting to show it's age a little. It looks like it needs a rehaul in the department.
• Hopefully, the company can grow and then have more frequent interactions with their customers.
• I am slightly wary that support may not have the same proficiency at the very highest level, as my company reaches the expert user level.

Incentivized

I had a lot of experience using erwin Data Modeler for designing data models. I think it's pretty intuitive and easy to use. It has enough features to represent your database requirements in form of a model.

Incentivized

CA customer support and our account manager have been able to support us with any issues that we have had, from managing our serial keys to issues we logged tickets to resolve. There are aspects of key management that have made it difficult over the years but support usually has worked with us.

Incentivized

Not listed, but I've only used alternatives built into something like the Squirrel SQL editor. That one is semi-functional but lacking many features and, in some instances, just plain wrong. The only pro there is that it's freely available and works over ODBC. I've tried some of the other free ones like Creately but didn't have much success.

Incentivized

InetSoft is a more cost-effective option that offers the same functionality, features, and usability. It is a great option, especially for SMEs. It also has top-notch customer service/support which is a key factor in selecting any agency or tool. I recommend using InetSoft especially for small businesses

Incentivized

• It is difficult to assign a monetary value to it. The initial learning curve was fairly long.
• It allows us to have better support documentation.
• It allows ease of communications between functional units.

Incentivized

• Reduction in excessive space for data storage repositories
• Faster time to analyse data and metadata. Quicker to reach objective analysis
• Conclusive informational reporting

Incentivized