IBM InfoSphere DataStage Reviews

We use IBM InfoSphere DataStage to extract data from different sources and perform business logic. It helps us in data transformation and loading into our data warehouse. The tool is also used for reporting purposes and selecting different extract files.

The IBM InfoSphere DataStage solution is user-friendly and easy to learn, which makes it convenient to work on. It supports business logic implementation. 

Additionally, it's useful for reporting and selecting different extract files.

Currently, the solution does not support cloud migration. We cannot connect to cloud tools using IBM InfoSphere DataStage. This is an area where improvement is needed.

I have been using IBM InfoSphere DataStage for ten plus years.

IBM InfoSphere DataStage is stable.

IBM InfoSphere DataStage is scalable.

I haven't faced any challenges with the technical support in version eleven point one. Previously, we faced challenges in version nine point one, but these were addressed after migrating to version eleven point one. 

I would rate the technical support ten out of ten.

Positive

I have not worked with any other solutions for data integration. My career has been focused on using InfoSphere DataStage only.

The initial setup was straightforward.

Our setup and implementation were done in-house by using the DevOps processes within our team. We rely on the DevOps and Jenkins tool for deployment.

If dealing with complex data, I recommend IBM InfoSphere DataStage. For less complexity, other tools might be suitable. 

On a scale of one to ten, I rate IBM InfoSphere DataStage as nine.

I work as a consultant and I have several projects with the Russian banks. My main expertise is building data warehouses and I use the product as a ETL. 

I am impressed with the tool's ETL tracing. 

It would be great if they can include some basic version of data quality checking features. 

The solution is quite stable. 

I would rate the product's scalability an eight out of ten. 

I would rate the product a nine out of ten. You need to get a balance between batch ETL processing and streaming. 

We started using this solution as we needed a system upgrade. We had to move the Db2 data to a AS400 system. 

Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface. 

We have been using this solution for a couple of months.

This is a scalable solution. 

When we have needed help from the IBM team, they were helpful. Our company is a premium partner so we get fast responses. 

Positive

The infrastructure and the software configuration part was done by one of my teammates. We were able to complete it in two working days. This was only for the installation of DataStage. 

I would advise others to identify the communication between servers and the client tools correctly. If working from a client environment and connecting to the server, configuration should be done correctly, otherwise you may encounter some issues.

I would rate this solution an eight out of ten. 

I am a consultant. I provide product information for our clients.

IBM InfoSphere DataStage is a good product.

It is quite useful and powerful.

From a practice point of view, solutions such as IBM InfoSphere DataStage and Oracle Data Integrator are losing ground, whereas open-source solutions are becoming increasingly powerful.

For example, we are currently working hard on several examples, and in a few years, open-source solutions will take the lead in the market. It will be used by large enterprises. 

Clients are looking for open-source solutions more and more.

It would be useful to provide support for Python, R, and Java.

I have more than 22 years of experience with many different products. 

It has been three to four years that we have been using IBM InfoSphere DataStage.

I have no issues with the stability of IBM InfoSphere DataStage.

Clients are quite dependant on support from the vendor. For example, if you want to activate a new feature on the product, you must create a ticket. You have no information on when it will be implemented, and the vendor does not know because they have a stream of tickets that are completed by the priority given to the ticket.

I am a consultant. I have different projects with different platforms. We are constantly going back and forth to different solutions for different projects.

I have had clients who have used Amazon Redshift.

Over the years, my clients have used many different products. For example, they use IBM Landscape and we use IBM InfoSphere.

The initial setup was straightforward. We did not have issues.

Comparable solutions will have common disadvantages, which is the total cost of the project.

It's quite expensive.

From time to time, I evaluate different products for my clients.

We have had different projects with three of four clients. The average term per project has been nine months and one year.

If you are working with an open-source solution or another solution, you can implement some features by yourself. For example, in the case of Amazon, which has Amazon Lambda, you can easily write your code in Python or Java, and it will orchestrate it. You can create your features yourself easily and gives you more abilities to make your solution run quicker, eliminating the dependence from the vendor.

I would rate IBM InfoSphere DataStage an eight out of ten.

The most powerful use of this solution is for full delivery integration. Aside from the ETL aspect, it makes data lineage. We are customers of IBM InfoSphere and I'm head of IT integration and finance transformation.

The key feature for me is the flexibility this solution offers. 

The solution is currently lacking virtualization ability. If they were to include it, it could be a good evolution on this framework. I'd like to see an improvement in support and a more customer friendly and knowledgeable support staff.  

I've been using this solution for over 20 years. 

Scalability is a question of licensing, but it can definitely be done.

Technical support could be better - more knowledgeable and customer friendly. 

We outsourced deployment to IBM and didn't have any issues. Implementation took about two weeks. We have between 20 and 30 users in the company and our maintenance is carried out by IBM.

We pay an annual licensing fee. 

Yes, we evaluated other tools, and this tool is competing internally with our PySQL development. It's a battle between code and local.

I rate this solution an eight out of 10. 

We use it for creating a pattern for data integration with our data vault. We have also used it for creating APIs.

As a data integration platform, it is easy to use. It is quite robust and useful for volumetric analysis when you have huge volumes of data. We have tested it for up to ten million rows, and it is robust enough to process ten million rows internally with its parallel processing. 

Its error logging mechanism is far simpler and easier to understand than other data integration tools.

The newer version of InfoSphere has the data catalog and IDC lineage. They are helpful in the easy traceability of columns and tables.

Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate.

In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere.

It was DataStage previously, and then it became InfoSphere. I have used DataStage for ten years and InfoSphere for one year.

It is quite stable. In the newer components of InfoSphere, you have a mapping tool called FastTrack and a metadata generator, which can have issues from time to time, but they get resolved.

It is not that easy to scale on-premises. I have worked on the ones deployed on Windows or Unix, and scalability is often dependent on whether you can add more CPUs or boxes. On the cloud, it would have been easier to scale. However, the current version can only be deployed on Windows or Unix.

I have not been in touch with them recently. Earlier, I was in touch with their technical support and had raised tickets because some weird errors, such as fantom error, were being logged in the error log, which made no sense. We used to get in touch with their support team to understand these.

I have used Informatica and SAS CA. IBM InfoSphere has the highest cost of licensing as compared to others. It is not very widely used, and it is very difficult to find people who have this sort of knowledge. 

The newer version of Informatica is on the cloud and is much more user-friendly than InfoSphere because it provides profiling information in nice graphs and charts. It also provides a lot of templates. For example, if I want to build a whole dimensional kind of structure, Informatica has a template. I just need to use that template. So, the ease of use is far better in Informatica, and it has everything that InfoSphere has. The only thing is that Informatica comes in bundles. That's the reason sometimes organizations don't go for it. For example, the data integration is a separate section, and the data quality is a separate section. They have separate pricing.

The initial setup is quite simple. It didn't take more than half an hour to set it up on my laptop.

I implemented it myself. In terms of maintenance, a particular version might not require any maintenance. There could be bug fixes and minor versions going in for some versions.

It is quite expensive.

I would recommend this solution for large-scale implementation where you need a complex transformation and data integration to happen according to a structured format, either a data vault or a dimension model. It is suitable for big companies because of the cost. It is a very valuable platform for data in large volumes. For small volumes, you have other open-source tools that can do the same thing for you.

I am part of a consultancy, and I have deployed this product for companies. We have five to eight developers. Because InfoSphere is a licensed product, and its licenses cost a lot, there are not many InfoSphere developers.

I would rate IBM InfoSphere DataStage an eight out of ten.

We are using this solution with enterprise customers for ETL (Extract, Transform and Load). The clients are just using it for retail processes.  

The ETL features are the most valuable to our clients.  

The product is pretty complex to set up. I think it is quite expensive. So, the set up could be simplified and the price could be brought in line.  

I have been using IBM Infosphere for 20 years.  

Once you have Infosphere up and running properly, it is stable.  

The product is definitely scalable.  

We previously worked with DataStage Informatica, we worked with Talend, we worked with SSIS, we looked at a lot of things in the course of providing solutions for customers.  

We probably work with SSIS (SQL Server Integration Services) more often because it is cheaper and easier to get hold of. More clients run SSIS than most of the others, but then most clients do not have massive workloads that require something more robust.  

It is quite a complex tool to set up properly in any environment. It requires someone who has experience with the product.  

My advice for anyone considering IBM Infosphere Datastage is to use a decent consulting house to help you once you get around to committing to the product. Do not assume that you will be able to go at this alone unless you have an extremely talented staff.  

On a scale from one to ten (where one is the worst and ten is the best), I would rate this product as a seven-out-of-ten.  

I'm an enterprise and information architect, and we're a customer of IBM. I personally don't use the product but assist companies in the market do for making the integration picture and design.

ETL is the most valuable feature, extract, transform and load. 

I think that performance monitoring could be improved. I know that my colleagues don't give good monitoring. I'm not sure if it's because of the product or because they don't do it normally, but performance monitoring is an issue. I also believe integration with the cloud is not so clear. It's typically a heavy system that people install on-premise. You can install it in the cloud, but it's not so straightforward. You don't find a lot of information unless you go to the IBM cloud. I think IBM is behind in cloud strategy, we would like to put it in the cloud, but there isn't much information about that. 

There are three things that could improve - the cloud, monitoring and cloud integration. It's a solid product but not a modern one and of course it depends what you're looking for. 

I've been using this product for 15 years. 

In the company I'm working with now you can see it's scalable.

We've been using the product a long time and hardly need technical support, which is great. We have very few problems.

I've never done an installation but I believe it's relatively complex, IBM usually is. 

I think DataStage is a product that one should look at as a good candidate in this segment.

I would rate this product a seven out of 10.