IBM InfoSphere DataStage Reviews

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. 

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 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 a solution provider and this is one of the products that we implement for our clients.

This solution has an end-to-end process used for data integration.

It's a robust solution.

The initial setup could be more straightforward.

We have been providing IBM InfoSphere DataStage for one year.

I believe this solution is stable. We have not received any feedback from our clients.

To my understanding, this solution is scalable.

We have several customers who are currently using it.

I have not contacted technical support.

We have a long list of different providers such as Informatica, IBM, Oracle, Microsoft SSIS, Pentaho, and Talend.

The installation was not straightforward and I would rate it at medium complexity.

The installation required assistance from an expert from IBM.

The price is expensive but there are no licensing fees.

Informatica provides a cloud-based deployment but we only work with the on-premises version. This is a product that I can recommend.

I would rate this solution a six out of ten.

We are supporting a healthcare domain vendor located in the US. We get data from various domains, such as health insurance. We have member data, provider data, and consumer data. We also have client-related stuff and broker-related commission data. 

We get the data from these domains, and after receiving it, we apply the transformation rules, such as joints. We also do the standardization of data by formatting and doing field validations, such as formatting the date field and doing data and time validations. We also do other normal transformations with some business logic. After applying all this, we send the data to the business.

We are mostly using transmission rules. It has a lot of functions and logic related to transmission. It is a user-friendly tool with in-built functions.

It doesn't have any big data connections. It would be good to have them because most of the systems are moving towards big data. There should also be a user-friendly way to interact with the cloud. 

Its loading process is very slow. It takes a lot of time for around 5 or 6 million records, and we are not able to provide real-time data to the vendors due to this delay. Its performance needs to be improved.

It is also like a legacy system. It is not updated much. In higher versions, they only do small changes. We would like to have new features and new technologies.

I have been using this solution for around 15 years.

It is easy to scale. In my project, six or seven people are using this solution, but in my company, we have around 15 to 16 projects.

We have an internal admin team for support. If they are not able to solve an issue, they raise a ticket with the IBM team. In the last ten years, we had to contact IBM only two to three times. Our internal team is able to handle most of the issues.

Its initial setup has moderate complexity. It required some coordination with the vendor because their system also needs to be ready. We also get maintenance support from them.

Our internal team takes care of group licensing and cost. We don't have individual licenses. We have group licensing at the company level. Usually, IBM doesn't charge anything separately on the licensing side.

For storage and everything else, we are paying around $6,000 per month, which is not very high. It includes Linux data storage, execution, and licensing. They're charging $40 for one-hour execution. Based on that, we are spending around $2,000 on the production environment and $1,000 on the lower environment for testing and development-side executions. For the mainframe, we are using the Db2 mainframe database, and we are spending around $1,000 on the Db2 mainframe database as well. All this comes out to be around $6,000. We, however, would like to have some cost reduction.

DataStage is a good tool for the ETL platform, but it is not suitable for a huge volume of data. It works well for low to medium volume of data. I would advise others to do a feasibility study and evaluate available options in the market in terms of features and cost.

I would rate IBM InfoSphere DataStage a seven out of ten.

We are a consulting company and we use this solution for our clients. We set up the data for them. We have various healthcare-related information from their vendor and business partners. They have integrated them and get data reports from it.

It improves how our client's organization functions.

We mainly use the designer and developer qualities. We use the basic features that we have.

They have many good features. The Hierarchical Data Stage is good.

The interface needs improvement. The interface in Informatica is easier than in DataStage.

The licensing can be improved. Many companies are moving away from DataStage because it is expensive.

The biggest issue that is unclear is how are they integrating into DevOps when they are binary files.

We would like to see DataStage integrated with DevOps so that a pipeline can be created for auto-deployment. Right now we are all doing it manually.

I have been working with IBM InfoSphere DataStage for seven years.

We have the 11.3 version but have recently migrated to the 11.7 version.

It's a stable product, it's not new.

It's very scalable. Our clients are medium-sized companies with a 1.5 billion turnover.

We reached out to IBM because the file was not readable, and they resolved the issue.

Technical support is good. I have not found any issues with technical support. I would rate them an eight out of ten.

In some cases, they have a delay in giving suggestions for the configuration.

Previously, in another company, I worked with Informatica. There are not a lot of differences but the interface is easier than it is in DataStage.

I don't do the setup, but I think that they have many challenges.

Initially, we had challenges with the configuration. We were trying to use the comparison for Excel, and reading the Excel files from the source, but the files were not readable.

It's very expensive.

I am not a developer, I have a team within our company for that.

There is a cloud migration strategy going on, so they are thinking of moving to the cloud. They want a tool that is not heavy and suitable for their budget.

The recommendation for using this tool would depend on the requirements. 

I don't have anything bad to say about this product.

I would rate this solution an eight out of ten.

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.

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.