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. 

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.

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 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.

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 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 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 implement this solution for our customers. The majority of them are Enterprise companies.

This solution is very easy to use because you can design to compile and to run.

The most valuable feature is the ability to transfer information via notes.

The documentation and in-application help for this solution need to be improved, especially for new features. By comparison, in Talend, there is help available for all of the features.

One of my clients has a problem using this solution with MongoDB.

In the next release of this solution, I would like to see the ability to copy and paste schemas. It would be very good because as it is now, you have to save the schema to a repository and then re-load it. It can be done in Talend, but in DataStage, it is not as good.

This is a stable solution. You have to be careful when you install a service pack because sometimes it causes problems. There may be a second service pack to solve problems that were introduced by the first one.

Scaling this solution is not difficult. When you first install you chose what components you need. My clients are enterprise companies, with at least five hundred or a thousand employees.

The are several technical support teams, and the quality of support depends on where the customer is situated. Normally, technical support answers quickly, but it can be improved.

The initial setup is not easy. You have to be an expert to install DataStage.

Sometimes I get calls from clients who ask me to install this solution because their Unix administrator is not able to do it. You have to configure your OS, Database, Web server, and more. There are a lot of things to install.  

If you are not experienced then it is not possible to install.

Small and medium-sized companies cannot afford to pay for this solution.

This solution is for larger companies. Smaller businesses use Talend.

This is a good product, but there is room for improvement.

I would rate this solution an eight out of ten.