IBM InfoSphere DataStage Reviews

The primary use case for IBM InfoSphere DataStage is related to standard business intelligence (BI) and extract, transform, load (ETL) operations.

DataStage is pretty good if the target is an IBM product like Netezza or Netezza on Cloud Pak. The optimization they do is much better compared to writing to non-IBM products. It generates highly efficient backend code to write data onto IBM systems, which I find valuable. The team was able to use it to address the requirements of the users.

They can provide better support for non-IBM tools when it comes to the target. Specifically, with Snowflake, there is no push-down optimization, which is a drawback when using DataStage.

I have had experience with DataStage for about three to four years.

I would rate their customer service and support at eight out of ten.

Positive

We did not switch over from a different solution. This is what we started with.

The initial setup was straightforward. It was a few weeks project to set everything up.

We are happy with what we are seeing. We are able to manage our requirements with the tool so far.

I do not have access to the pricing or standard licensing fee information.

I was exploring and came to PeerSpot to evaluate different solutions.

For our requirements, we are able to manage with DataStage, and the support is good. I would recommend it to others. 

I rate the overall solution an eight out of ten.

We have integrated multiple data sources into a single data warehouse. For this, we used to build complex ETL jobs and datasets to integrate data from multiple sources into a single data warehouse. So, these are basically the use cases.

In IBM DataStage, the Transformer is the most valuable feature for me. It enables me to apply complex transformations, generate the gateway key, and map source tables into the session table.

So, there are some features that are missing. If I compare DataStage to Talend, Talend allows you to write custom code in Java or use these tools in your applications as well if you are building a job application. But in DataStage, it does not allow you to write custom code for any component.

Moreover, Talend allows you to extract Java code and call it in your APIs or applications, DataStage does not have this feature.

In future releases, DataStage could benefit from the ability to save metadata into a database. So, if the database crashes or you lose the data in the database, you could recover it. Unlike files, which are harder to manage.

I have been using this solution for five years. 

I would rate the stability of this solution a seven out of ten.

I would rate the scalability of this solution a five out of ten. It should be improved. We have almost eight end users in our area. Some are engineers, one is an administrator, and two of them monitor the pipelines. The rest are developers.

We plan to increase the further usage. 

In terms of documentation and support, IBM is reliable for providing support to its partners or those with licenses. You can easily find problem resolution support online.

Positive

I have previously worked on SSIS. After using SSIS, I moved to DataStage. We explored IBM DataStage for our specific needs.

I would rate my experience with the initial setup a seven out of ten, where one is difficult and ten is easy. I have worked both on-premises and deployed it on a private cloud.

The deployment process usually takes a day.

For deployment, you first need to install DataStage on the desired server. Then, you have to take a backup of the development and deploy it on the server. After importing, you need to execute and schedule it through your job application.

People required for the deployment depends on the scenario. Sometimes, one person is more than enough for deployment.

Pricing is handled by the procurement department. But compared to other enterprise tools like Informatica or Pentaho, IBM DataStage is quite cheaper.

I would highly recommend this solution because of its shared-nothing architecture that it uses, the capabilities it offers, and the fact that every feature has its own use. For example, it has a Director for creating jobs, clients for monitoring and scheduling jobs, and an Administrative client for administration purposes. This is something well managed by IBM.

Overall, I would rate the solution a seven out of ten. There are certain areas of improvement.

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.

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.

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.