IBM InfoSphere DataStage Reviews

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. 

The primary use case is for ETL purposes for when we're building data warehouses or data marts. We use it to get the data from different disparate sources, do some ETL on them, and we use DataStage and then load them into the data warehouse, database, or data mart.

This solution used to be on-premises, but they've recently come out with a hybrid offering.

The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms. I have not found those in Informatica or Talend.

As a product, it needs to be more stable. It's a legacy product, so even though it's high-performing, it's not very stable compared to other products like Informatica or Talend. The UI also looks dated.

In the future, I would like to see more integration with cloud technologies. Technical support could be improved.

I've worked with DataStage for about 9 years.

The stability could be better.

It's scalable.

I would rate technical support 6 out of 10.

For the on-prem solution, it was moderately complex. I'm not sure about the hybrid version.

I would rate this solution 8 out of 10.

We primarily use the solution for ETL jobs and movement of data.

The solution has improved the time it takes to perform tasks related to batch applications.

The parallel job scan has been a very valuable feature.

The solution should be more user-friendly.

The solution is quite stable.

I've never investigated the scalability, but I can say that it only scales on the machine. I can have three machines running in parallel. We have about 20 people using the solution, and they are mostly developers and admins. We mainly use the solution for APL jobs.

On a scale of one to ten, I would give technical support and eight.

We were mostly using ETLs on mainframe jobs.

It's a straightforward process. In terms of deployment from the data stage, it takes about a week.

We use an integrator to assist with implementation.

The advice I would give to others is to make sure they define a framework for development and for management. This could be very useful for the future of the product in the company.

I would rate the entire solution eight out of ten. I really like DataStage. The product fits our requirements perfectly.

We are changing the product now, however, to a cloud-based approach for DataStage.

We primarily use this product for data loading. We take data from different applications and databases and put it into our data warehouse. 

The most valuable feature is the data integration for data warehousing.

The response time from support is slow and needs to be improved.

I have been using InfoSphere DataStage for almost eight years.

This is a stable product.

We have almost 30 people who use InfoSphere DataStage.

Technical support can be slow.

This product has a lot of good features.

I would rate this solution an eight out of ten.

DataStage itself is a very powerful tool and you have a lot of transformations that you can do. In comparison to Informatica, you can run very complex transactions on it. It's a precise and powerful environment. And when you have ETLs and you all your data documented on the data manager and you have the rest of management from IBM itself on InfoSphere, it's very powerful, especially when you use the whole suite. It helps with end-user technologies and gives you better imaging. 

It's powerful in administration mode. It works well when you're using solutions like DataConnect, IBM CDC, etc.

DataStage works better with Linux operating systems when the application services are hosted on a Linux system equipment, but it's powerful on Windows too.

Also, no matter what language you use, you can always transform the data.

I'm not sure about the latest versions, however, as I'm on 11.3, which is about five years old.

I really like this tool, but the administration should be on the same client application because a lot of administration features are not on the client-side, and they usually need to have administrative access. It's quite complicated to force IT, teams, to have separate administrative access from the developers. 

The platform also needs more stability. It caches a lot. It crashes on the application servers that the host allows on the platform.

The solution needs better online tools for data, or for sourcing data on the internet. They have InfoSphere exchange but it's not as useful for DataStage. 

The stability is related to the operating system your company uses. It crashes occasionally when you're hosting the application servers, but only in the servers on the operating system. With Linux, because Linux itself is very robust, it crashes less. For example, we have a telecom with 40 million users and using Linux it crashed maybe two times a year. However, when the solution was hosted on the Windows platform, it crashed two to three times a month. 

The crashes are related to memory and if it's not automated, you have to deal with it manually. On Windows, you have to release the cache memories manually, but on Linux, you don't have to do that, which is why you get less crashing. 

The solution is very scalable, but at a certain point, it consumes a lot of resources. In order to scale, you need a lot of memory and a lot of people.

The quality of technical support you can expect usually depends on the region. In Egypt, it was not great, but in Jordan, Dubai, and Kuwait, it was good. That was a couple of years ago. I'm not using the solution right now, so I can't say for sure if this is still the case.

The solution has one of the most straightforward setups. It's even easier than Office.

The last version I interacted with was 11.3 because the later versions were cloud-based and usually our customers didn't want to use the solution on the cloud.

In terms of advice, I would give to anyone trying to implement the solution is this: you to have accurate sizing. Clients always do the sizing wrong and they need more experience to get the sizing right. Setting up the environments takes sizing into account but it usually makes a lot of problems if the sizing is poor when it starts to operate. Then you have re-implement and it will require an increase in resources that will change your budget. 

I would rate this solution nine 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.

My company is a consulting firm and I'm a managing partner. We consult for large size companies in the telecommunications, banking and insurance sectors. We partner with IBM. We're not using the latest version of DataStage but one of the more recent ones. I use the product for a migration project. It's a DB2 to Oracle migration project and the source database is mainframe. I need DataStage for that purpose.

I think the ETL tools are the most valuable features. It has an IBM tool, a friendly UI and it makes things more comfortable. A second good feature is that after you make some ETLs, migrations source to target, DataStage is capable of providing details and extracting data. The push down feature is also a valuable feature. 

The price would be the first thing I would want to change. Reduced cost would allow more customers to choose the product. It's quite expensive in relation to the cost of other similar solutions. I think it would also be helpful if the product was more adaptable to other platforms and vendors. I would also like to see an improvement in support. 

I've been using the product for more than two years. 

The product is stable. 

The product is scalable.

We do sometimes have issues in terms of support with regard to IBM products in this country. It's difficult to get what we want and it could really be improved and made more efficient. 

I recall that the setup was quite difficult. We had to call in some IBM people. It's possible that they have improved that aspect. I know there's a difference in installation depending on whether it's on-prem or cloud. It's possible that the cloud version is easier to install but I don't have experience with that. 

I would rate InfoSphere an eight out of 10. 

It is in the environment of our client, who is a large Russian bank. They are in the top 20, as of August, and have the re-maintenance project of their data warehouse solution based on IBM technologies. They use IBM BWD, a banking data model, on Netezza and DataStages in ETL tools. It is a native case.

We are using the on-premise deployment model.

Our main goal of this project is to increase the efficiency of the usage of this solution and help the bank to get money from the data.

The data lineage report can be filtered for reporting. The reports are user-friendly and take less time to find what you need.

It is a powerful tool with parallel data streams.

The previous project was based on Microsoft SQL. It moved huge amounts of data from different data sources and DataStage to a middle stage, then moved it to Netezza. This created a bottleneck in the solution. We are trying to streamline it and create ETL processes. These will take data exactly from the data sources and move them to Netezza without using of a middle database. The volume of data is quite detailed. We are talking about records in the tens to hundreds of millions. 

We would be happy to see in next versions the ability to return several parameters from jobs. Now, jobs can return just one parameter. If they could return several parameters, that would be great.

We would be happy if the IBM could give us more tolerance for bad networks or VPN channels, as this happens from time to time.

It would be great if we could use more than one SQL operator in the Source DB connector stage. Currently, in the target DB connection stage, we can use several SQL operators, but in the Source DB connector stage we can use only one. It would be better if we could use several.

Data Vault is become more popular. It would be great if it appeared in the newest versions.

I would like them to have more database procedures.

It is quite stable. I haven't seen any pop up errors. It works properly.

They fixed some bugs in version 11.5.02. It works well now.

It is quite scalable. 

DataStage is okay, but the problem of scalability is with another component of the solution (Netezza). The main problem is with the client version of Netezza. IBM stops to support it, then they tell us that we need move to the next version of Netezza. However, the price is too high for the client and we need to look for another platform. 

The client thinks that Datastage can stay in place with another platform.

There are not more than five data analysts and administrators using DataStage because it works at night with ETL processes. Therefore, end users are not using it. The several people who maintain and administer it are the users. 

We have two data specialist who work with it. From the bank, there are about five people who use it.

I haven't used the technical support.

Our client previously used SSIS from Microsoft. They also used Oracle. However, they did not have a special solution for ETL. Ten years ago, they used another data warehouse solution which used XML files as a transport layer.

DataStage is a directly specialized ETL tool which has instruments built for the ETL process as a stream. It can visualize and can track the ETL process, integrating it with the data governance catalog along with other IBM instruments. Previous solutions, except for SSIS, were just a number of scripts which created a process like peer-to-peer. It wasn't a centralized ETL tool with centralized ETL governance.

It was straightforward technically.

Three to four years ago, they decided to start a new data warehouse project. They were working with another Ukrainian company, which engineered this solution. However, the solution hadn't made it to production because of some problems between the understanding of IT and business. They tried to move it to production several times. After that, they decided to do some technical audits for this solution. They& asked us to come and see the solution, then write the audit report, which we did. Then, they asked us what to do with these problems, and this is when we began to help them.

All the components were already in place. We changed it a bit, tweaked the ETL processes, and changed some structures in the data warehouse. This solved the current needs of their business. 

The deployment is continuous. We are working on this project currently. It should take another year. At the moment, we have some Agile processes, in which we are finding new business needs. We try to understand them, then deploy the current user story.

The main problem of this project is they are trying to move the old solution to production in order to begin getting return on investment.

There were no problems with the licensing model for the bank.

It is the best solution in the IBM environment. It uses IBM data models, such as data quality tools.