IBM InfoSphere DataStage Reviews

We are a consultancy company, so we are not using DataStage for our own purposes. We deploy it for our customers. We use it to supply data integration and data warehousing solutions based on the specific needs of clients.

The product has improved our organization by allowing us to provide the product to clients as a reliable data management solution.

The product is a very powerful data management tool and the ability to run it in the parallel mode makes it very, very fast. I would say that the ability to use parallel mode would be one of the most valuable features.

The features that could be better starts with the user interface. It has been getting better in the last releases and in the past few years, and I guess that they will continue to make progress on this front. But even with the improvements that they have made, it could be even better now, and really should be. I think it's a little bit difficult to use because of the interface. Being user-friendly is important for any product and they need to make this adjustment.

In addition to improvements in the base user interface, I would say it would be good to incorporate more interface options for cloud-based systems.

The product is very stable. The stability enhances the fact that it is powerful and fast, so it is a reliable solution with good performance.

I feel that the product has excellent scalability. We currently have more than 15,000 users as clients worldwide and scalability has never presented as an issue. It's used in the U.S., in Asia, and in Europe, so it seems to perform in various markets satisfactorily.

It's an enterprise-enabled product, so with that designation, it really needs to be scalable to satisfy the needs of clients — and those needs change all the time. It has the ability to connect reliably to a lot of sources and this is a very, very important thing for people who are using it.

We do have some experience with technical support and customer services. We have access to the IBM software hotline, which is normal for IBM.  They work with the FTS (Follow the Sun) support model which means they are available 24/7. The availability is good and the response is as well. I would say it is good support.

The initial setup of the product is straightforward. The first deployment may be more complex in one case than another. It depends on the complexity of the processes an organization is building and what they need to consider in future planning. Normally you can install it without much trouble and have your first processes live within a few days.

After that, the project is ongoing and it becomes more complex as you build it out. Normally everything does not have to be in place from the beginning as the solution may be deployed to solve new or future issues. In other words it is not replacing something that is already functioning, it is providing something new. As you build out, you get more processes going and the setup becomes more complex. But the initial setup is quite simple.

We do the deployment with our own team for the client, but the implementation can change depending on the client needs. When the client has specific things that need to be resolved for their situation or they want to install and to implement additional products to integrate with the base solution, that affects the rollout. It's especially true during the implementation stage. The implementation team can begin with as little as one person and it can end up as a team of five, six, or seven members depending on complexity and needs for rapid deployment. It also depends on whether the product is going to be used throughout the company. There are a lot of customers who deploy globally or selectively because they may have a strategy already in place for certain solutions that they may not want to change. For example, they may already have ETL processes being used without DataStage and it may not make sense to convert these processes.

It is very difficult to say how much the product costs because there are variables depending on the configuration. Normally it's priced according to use, so the price can vary quite a lot. The more you use, the more you pay.

In comparison to other products, I would say it's not so expensive as Informatica, but it is intended to be an enterprise solution so it's not very cheap to deploy as products that are not enterprise solutions.

The products we offer are really very different in pricing compared to open-source products. With open-source you have only the maintenance cost. For the software products we use, you have to invest in the software and then the maintenance costs are in addition to that.

There are no other costs in addition to the standard licensing fee and the maintenance. With IBM, you typically pay for the licenses and the first 12 months of maintenance is included in that cost. Afterward, you pay for the maintenance year-to-year.

We currently also use PowerCenter from Informatica as a solution for some clients. It isn't really a previous solution or a solution we evaluated and discarded but it is one that we sometimes use instead of DataStage. It depends on the needs of our customers.

The decision on which product to pick has partly to do with what the client wants to do and what we believe is the better solution for them and their needs. We have some projects where we use PowerCenter simply because our customer wants to use it; we have other projects where we use DataStage because of some of these customers are already using DataStage or they prefer it because it is from IBM.

In a similar way, we sometimes use Microsoft Integration Services, which is a very small part of our business. But again it isn't so much that we evaluated the solution and dismissed it or switched from using it. These products are opportunities for us to choose between in order to provide the best solution for clients. We evaluate the options and choose the best fit for the project.

I would rate this particular product as a nine out of ten. It is very powerful and very fast, but the problems with the interface make it less than perfect.

As far as other advice that I would have for other people considering this as a solution, the first and most important is to examine your needs and decide on the processes you want to build. From that, you can immediately have a better idea of the type of solution that might be best for you. Then it is a good idea to get the advice of a consultant — like us.

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.

There could be more customization options for the product.

We have been using IBM InfoSphere DataStage for 20 years. At present, we are using version 11.7.

I rate IBM InfoSphere DataStage’s stability a five out of ten.

The product is suitable for enterprise companies. We have 100 users for it. I rate the platform’s scalability a seven out of ten. It is easily scalable compared to other systems.

The complexity of the technical support services depends on the contact person. Sometimes, it is a good experience, while sometimes a poor experience communicating with their executives.

Neutral

The product is easy to deploy. I rate the process an eight or nine. The deployment time depends on the specific requirements of customers. It takes approximately three months to complete. It requires a team of five to 100 people to execute it, depending on the company size.

The product is expensive. I rate its pricing a ten out of ten.

I rate IBM InfoSphere DataStage an eight out of ten.

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.

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.