IBM InfoSphere DataStage Reviews

IBM InfoSphere DataStage was mostly used for ETL and data integration purposes, so extract, transfer, and load, including some data quality use cases. My team used the solution to extract data from various sources, do some business transformations, load the data into a target database, or generate files.

The best feature of IBM InfoSphere DataStage for me was that it was very much user-friendly. The solution didn't require that much raw coding because most of its features were drag and drop, plus it had a large number of functionalities.

What needs improvement in IBM InfoSphere DataStage is its pricing. The pricing for the solution is higher than its competitors, so a lot of the clients my company has worked with prefer other tools over IBM InfoSphere DataStage because of the high price tag.

Another area for improvement in the solution stems from a lot of new types of databases, for example, databases in the cloud and big data have become available, and IBM InfoSphere DataStage is working on various connectors for different data sources, but that still isn't up-to-date, meaning that some connectors are missing for modern data sources.

The latest version of IBM InfoSphere DataStage also has a complex architecture, so my team faced frequent outages and that should be improved as well.

I've been working with IBM InfoSphere DataStage for more than seven years.

IBM InfoSphere DataStage is a stable product and it's been in the market for quite some time, but in its latest version, there's been some instability caused by the new features introduced in the solution. The architecture was changed a lot and that was causing issues and frequent outages that my company had to go back to IBM for troubleshooting. My team didn't face issues in the earlier version of IBM InfoSphere DataStage. It was the latest version that had instability issues.

IBM InfoSphere DataStage is a very scalable product.

IBM InfoSphere DataStage has a pretty good technical support, but with the new version, particularly the new architecture and the microservice concept, support sometimes takes a bit of time, even for the IBM team to figure out what's wrong, but once that's been figured out, the team comes up with the solution or with a patch.

Setting up IBM InfoSphere DataStage was easy.

How long the deployment takes would depend on certain factors, but it usually takes just two to three hours.

I have no information on the exact pricing for IBM InfoSphere DataStage because the solution is usually procured by the clients my company works with, though the pricing is higher compared to other solutions, so many clients choose to go with a different solution rather than IBM InfoSphere DataStage.

The last version of IBM InfoSphere DataStage which I've worked with was version 11.7.

I work for an IT service company that works with multiple clients on multiple projects, so close to two hundred people use IBM InfoSphere DataStage for various clients.

Per project, on average, three people take care of IBM InfoSphere DataStage deployment, maintenance, and support-related activities.

My advice to people looking into implementing IBM InfoSphere DataStage is that it's a very good product. A lot of similar products have come up nowadays, but this product has a pretty good reputation as it's been in the market for quite a while. I do think other products such as Talend, Informatica PowerCenter, and Informatica Data Quality are better than IBM InfoSphere DataStage.

My rating for IBM InfoSphere DataStage is eight out of ten.

My company has a partnership with IBM.

The solution is mainly used for, marketing campaigns, customer segmentation, and home loans.

The most valuable feature of the solution is the ability to incorporate very complex business rules in Data Stage.

The solution can be a bit more user-friendly, similar to Informatica.

I would like the solution to have some basic streaming functionality added.

I have been using the solution for one year.

We don't currently have much in our production environment. We are gradually moving into production, so whatever small setup we have is okay for now. I'm taking the overall perspective into account and I think we do have dependencies on the other jobs. This is purely based on the feedback we receive, which sometimes means that we're not able to run our process because there are dependencies, similar to other jobs also. The jobs don't complete on time. We received feedback that there was a problem handling data, which caused jobs to fail and needed to be rerun. This could be product-specific, design-specific, or anything else, but I think there is room for improvement in terms of stability. I would give the solution a seven out of ten.

I think that scalable systems should also have good performance. The scalability of this solution in my opinion may not be on the same level as Informatica Power Exchange Data Integration.

I give the scalability of the solution a seven out of ten. We are facing problems whenever we have huge amounts of data and there are job failures. We need to take care of how to tackle that situation. 

We didn't need to do anything because the customer, with whom we are working on the project, had already set everything up for us. The initial setup was not in our preview.

I give the solution a seven out of ten.

We have a separate platform team or support team. In case of any query, it used to be routed to this team, which was internally used to deal with the Data Stage people.

I'm not a technical expert because I haven't been a developer for 12 years. This is what I understand from the feedback I've received. Informatica Power Exchange Data Integration is much better from a scalability perspective, compared to IBM InfoSphere Data Stage. Scalability, user-friendliness, and inclusion of different business rules are all important, but I think Informatica Power Exchange Data Integration gives us one step further on that.

Right now, I'm working for a telecom company. So, we are using IBM InfoSphere DataStage for constructing ETL jobs for them so that they can load data from their various different sources into their warehouse.

The valuable feature of the solution is, I think, its functionality. So, there are a lot of transformations that you can apply by just using a transformer. Also, you don't need to complicate your SQL queries while trying to transform your data. Hence, the transformer is something I like in the solution.

I don't know if it's just a problem with me, but the issue I see is that when we connect to the server from the client, especially when you're going to run a job or something, the whole connection is really slow. It takes a lot of time to actually trigger your job and then go into the logs and other stuff. So all of this is really time-consuming.

I have been using IBM InfoSphere DataStage for five years. Also, I am using IBM InfoSphere DataStage Version 11.7. My company is a consultant for DataStage.

Most of the time, it is stable. Sometimes there are some issues you don't understand and go away when you have a read-only job. But that is quite rare. Other times, it seems quite stable.

The solution's scalability is really good. In terms of parallel jobs, we are using multi-instance jobs where you can scale them easily.

In my company, my team is spread across multiple countries, including Pakistan and India.

I haven't contacted IBM's technical support.

The solution's initial setup is straightforward. Also, it's a one-time activity. It is better to have a competent person for deployment since newbies cannot do it themselves.

When I started using IBM InfoSphere DataStage, it was already deployed on the server. So I did not have to go through the installation phase.

ROI is something that the client takes care of, and I think they must be keeping track of it and getting a certain result indicating a good ROI. So, that's why they may have continued using it over the years.

Before DataStage, I did not evaluate other options. Our client was already comfortable with DataStage, so that's what we had to use.

I recommend that other people who want to use it go for DataStage on the cloud. The on-prem version of the solution looks and feels old. Also it's time-consuming as well. Overall, I rate the solution a six out of ten.

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 primarily use the solution for the UTS tool as well a for billing and data. We use it to clean the data from different systems and for pulling in data.

The solution is good for bringing in data from third-party systems.

Various aspects of the solution are valuable, but it often depends on the use cases.

Finding logs is very easy on the solution.

Overall, compared to SAS or Informatica, the solution is much easier to navigate.

The mod options should be simplified. Some options on DataStage aren't working properly.

The solution needs to lower its price.

The template mapping could be easier.

The solution should allow for compression of data.

I've been using the solution for about 12 years.

Typically, the solution is stable.

The solution is scalable. We have about six or seven clients using the solution currently.

We've never been in direct contact with IBM's technical support. We use a third party, so if we have issues, we turn to them for troubleshooting.

We previously used tools such as Informatica. We've also previously used SQL for billing.

The initial setup is easy for the DataStage, but for billing and metadata, it gets more complicated. In our case, before installing the metadata, the proper documentation was not there, which complicated things a bit.

We handled the implementation ourselves.

The solution is quite expensive in comparison to similar solutions.

We did approach other vendors before ultimately choosing IBM.

We use the on-premises deployment model.

If you are comparing the solution to Informatica, this solution is much simpler. In Informatica, for example, there might be two to three ways to find a log, but with DataStage, they make it much easier. However, compared to other vendors, IBM's licensing costs are more expensive.

I'd rate the solution eight out of ten.

IBM InfoSphere DataStage is a core ETL tool. We use it with source systems like mainframes. DataStage is perfectly suited for extracting data from mainframes.

IBM is stable and accurate to monitor. It's easy to understand to monitor the data lineage from source to target.

DataStage is quite expensive. It is too hard to find a consultant using DataStage in Turkey.

I have been using IBM InfoSphere DataStage for three years. I also used this solution for two years back in 2009-10.

The product is stable.

I rate the solution’s stability a nine out of ten.

I rate the solution’s scalability an eight out of ten.

The quality and response time of support is fine. It's pretty quick.

Positive

Informatica is the first choice for me. It's easy to use and not so expensive compared to DataStage.

You install IBM InfoSphere DataStage once you've set it up properly. It's robust and reliable, but initially configuring it can be challenging.

The first consideration is the type of source system they have, whether it is a mainframe or not. Another key indicator for me to suggest DataStage is if the client has other IBM ecosystems, such as data quality or IBM governance tools. This makes it highly suitable because you can easily establish data lineage.

Overall, I rate the solution a seven out of ten.

The product is primarily used for  intense data transformation; it's part of the risk management, and dataflow, and is sourcing data from the data warehouse on the SAP Sybase platform.

The connectivity with the databases and the speed and flexibility of modeling is excellent. We like the flexibility of modeling.

The solution is stable.

It can scale.

We'd like better integration with source control and error and diagnostic information. The error messaging needs to be improved. 

The solution is a bit complicated. 

I've been using the solution for four years. 

It's stable. it's reliable. There are no bugs or glitches. It doesn't crash or freeze. 

We can scale the solution as needed. 

There are about 50 users on the solution right now. 

While technical support may have been used, I have never personally dealt with them.

I've used SSIS as well and find this product to be more difficult to set up.

The initial setup can be challenging. It's harder to set up than, for example, SSIS.

I'm not sure how long it took to set up, as it was already in place when I joined the team. However, I would say it took a week to deploy.

We have five people on hand that can handle deployment and maintenance tasks. They are all engineers. 

The initial setup can be handled in-house. 

The licensing we have is permanent. 

I'd recommend the product to others. 

I'd rate it a nine out of ten. We've been pleased with its capabilities overall. 

Complex data integration projects which require integration from multiple data sources.

I have worked during many implementations using DataStage. All of the projects that I worked on have been successful. This is due mainly to the strict discipline around best practices, and by following a set of standards and templates designed to reduce complexity and improve automation, including strong reference architecture.

• Its parallel processing capability allows you to go through extremely large data sets in no time at all, if you do your job right. 
• Highly customizable: Allowing you to handle multiple data latencies (scheduled batch, on-demand, and real-time) in the same job. 
• High scalability: Start small and go big with the same job. You just need to adjust the configuration file, no need to recompile.
• Strong metadata management: Business, technical, and process metadata can all be managed from a single place.
• Ease of integration with other tool sets: Easily supports APIs (or build your own) to support data streaming (or batched) from other systems.
• Data Quality Management from within the tool: Supporting data sampling, including profiling of data, directly from the development canvas.
  

High-cost of ownership: They could take a page from open source software, such as Talend.

Working with some of the big data components is good, but I can see improvements are needed, such as native support for Spark and HBase.

No issues.

No issues.

Support is always good.

Have used quite a few ETL tools in my job.

• Ab Initio: Even pricier, but has a highly competent ETL tool. It is complete, but hard to use. 
• Informatica: Not as flexible and does not support the same level of complexity in its maps.
• Talend: It is a good tool suite, extensive, but can be cumbersome to cite all its pieces.
• ODI: For the Oracle centric world.
• SSIS: Week when compared to any of the above tool sets.

Depends on type of environment that is being installed. I have seen fairly simple to overly complex initial setups due to the environment, not due to the tool.

Both vendor and in-house team implementations:

IBM has top-notch support and tool services along with other partners as well. Depending on the partner, this can go from installation and configuration to solution development, etc.)

Most in-house teams that I have seen tend to have have good developers, but not always good architects. Like most every data integration project, if you do not have a strong architecture, your solution will eventually fail.

Depends on the project.

Have done many ETL tool evaluations based on client requirements. DataStage has always been in the top-three. It may not have been selected due to different weights being used for different sections of the evaluation for different clients, but it has always been in the top-three consistently.

If you have the budget and your solution requires industrial/enterprise strength data integration, this product is always a good choice.