We tend to use the latest version of the solution.

We are considering the cloud. We are currently debating whether we need to go to WhereScape or drop WhereScape and we go to the cloud. I've been asking about their host-ability and version controllability if we move to the cloud and they were not giving too many promising answers. Basically, when we go to cloud viewer, we want it to go completely on a platform as a service, not infrastructure as a service, as IaaS is a little more costly than PaaS - The Chinese PaaS. 

Also, we would like to use, as a team, seven or eight people at scale - not just on the server installed and then use it as one or two accounts. The whole stability issue on the cloud needs a little more clarification.

I'd advise companies considering the solution that, if it is on-premise and they have a good volume of data coming, it can be easy to start using it. I'd say that negotiating is important and making sure that the pricing is clear, as they can come back and alter the price after the fact. 

Other than that, if you had a lean team, I would say go for Wherescape. It's simple, straightforward, and not too complex. That said, if you have more XML semi-structured data, or unstructured data, you might want to look for some other product.

I'd rate the solution at an eight out of ten.

WhereScape RED has been a great fit for my organization.

The compelling selling point for this and similar tools as "datamart in a box" providers is that they are pre-built frameworks and documentation. The opportunity is that staff with little data warehousing experience can get up to speed easily and not have to worry about building logging, orchestration and error frameworks or even know much about data warehouse design.

Unfortunately this tool's basic architecture has severe flaws which make it likely impractical for most real world marts or data warehouses. It has some significant cons in the following areas:

- Metadata support specific (cannot share across multiple) target database

- Unreliable lineage

- Lacks capability to interface with application API's

- Lacks out-of-box CDC control capabilities

- Poor/outdated GUI (looks like early 1990s)

- Lack of available resources in the market place who can operate this tool

- Lack of customer base and information available

- Primitive logging and error handling

- Forced duplication of staging data multiple times

- Inability to separate source data capture from targets (tightly couples sources with targets)

- Stores all objects in single target database causing number of issues such as backup/recovery, fragmentation, limited organization options for objects

No solution is perfect and I could probably find nits here and there, however, I find WhereScape RED to be exactly what I was looking for. Roughly 80% of a data analyst's job is preparing data and 20% is doing the analysis. I purchased WhereScape RED to flip that equation on its head.

I highly recommend engaging with WhereScape service consultants during adoption of RED. Learn the best practices they promote, and live by them to get the best results.

For the cost it has a very effective bang for buck. See comment about new owners. 

I would recommend this product to new users. 

On a scale from one to ten, I would give WhereScape RED a seven.

As other reviewers have noted, data warehouse automation requires you to change your thinking and perspective somewhat. If you are looking at this product as a simple replacement for your existing ETL and try to use it exactly the way you used ETL, then you will not fully realize the functional benefits (the cost benefits will still be there though). You need to think more in terms of agile data warehouse design. For those new to this concept, I recommend a book called “Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema” by Lawrence Corr and Jim Stagnitto. WhereScape fits very nicely into the concepts presented in the book.

I would not hesitate to say that if someone has really limited time for a project it can make a difference and you can have the data ready for use in a very short period of time. This can be a lifesaver. I will rate this solution a seven out of ten. 

Don't confuse data warehouse automation with ETL automation. DWA automates the entire data warehousing life cycle. Change your approach (think agile), change your processes (think end-to-end ... source data to business impact), and change your perspective (think cyclic, not linear). Without these changes you miss out on many of the benefits of automation.