IBM InfoSphere DataStage vs StreamSets comparison

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IBM InfoSphere DataStage

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Executive Summary

We performed a comparison between IBM InfoSphere DataStage and StreamSets based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM InfoSphere DataStage vs. StreamSets Report (Updated: May 2024).

IBM InfoSphere DataStage vs. StreamSets

May 2024

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Categories and Ranking

IBM InfoSphere DataStage

Ranking in Data Integration

7th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

StreamSets

Ranking in Data Integration

8th

Average Rating

8.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Market share comparison

As of June 2024, in the Data Integration category, the market share of IBM InfoSphere DataStage is 6.6% and it increased by 6.5% compared to the previous year. The market share of StreamSets is 1.6% and it increased by 29.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

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Featured Reviews

Murali B

Data Engineer at Ernst & Young

Mar 28, 2024

Facilitated our peak data integration projects, offers good GUI and availability of connectors is strong

DataStage facilitated our peak data integration projects. For example, big data integrations have happened, particularly when we worked with BigQuery files... that integration server. DataStage parallel processing capabilities have improved data tasks. When I worked with DataStage, it could handle around two terabytes of data. We have other appliances as well, but we're processing data concurrently. It was good. My team supported it well, and everything worked fine. The GUI was good. Compared to Cloud Pak for Data, we have some enhanced connectors in the standard InfoSphere DataStage version. That standard version is really good; it's easy to use. When we want to find out the absolute quality of data, the governance features really helped. For example, when we tried to identify discrepancies between systems, it worked well.

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Nantabo Jackie

Sales Manager at Soft Hostings Limited

Mar 24, 2023

Simplified pipelines and helped us break down data silos within our organization

The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The product is easy to deploy."

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

"The solution is stable."

"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"

"The ETL tools are probably the most valuable feature. It has an IBM tool, a friendly UI and it makes things more comfortable."

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

"We like the flexibility of modeling."

"The solution is very easy to use."

More IBM InfoSphere DataStage pros

"It's very easy to integrate. It integrates with Snowflake, AWS, Google Cloud, and Azure. It's very helpful for DevOps, DataOps, and data engineering because it provides a comprehensive solution, and it's not complicated."

"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."

"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."

"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."

"The UI is user-friendly, it doesn't require any technical know-how and we can navigate to social media or use it more easily."

"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."

"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."

"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."

More StreamSets pros

Cons

"The graphical user interface (GUI) feels a lot like the interfaces from the 1980s."

"Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface."

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

"Working with some of the big data components is good, but I can see improvements are needed."

"There could be more customization options for the product."

"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."

"The initial setup can be complex."

"In terms of intermediate storage, we have some challenges, especially with customers who store data in intermediate locations."

More IBM InfoSphere DataStage cons

"If you use JDBC Lookup, for example, it generally takes a long time to process data."

"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."

"Using ETL pipelines is a bit complicated and requires some technical aid."

"We've seen a couple of cases where it appears to have a memory leak or a similar problem."

"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."

"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."

"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."

"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."

More StreamSets cons

Pricing and Cost Advice

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

"It is quite expensive."

"The pricing is competitive but on the higher side of the pricing scale."

"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."

"The product is expensive."

"The cost is too high."

"Pricing varies based on use, and it is not as costly as some competing enterprise solutions."

"It's quite expensive."

More IBM InfoSphere DataStage pricing and cost advice

"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."

"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."

"StreamSets is expensive, especially for small businesses."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"The overall cost for small and mid-size organizations needs to be better."

"The pricing is good, but not the best. They have some customized plans you can opt for."

"We are running the community version right now, which can be used free of charge."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Manufacturing Company

11%

Computer Software Company

10%

Insurance Company

Financial Services Firm

17%

Computer Software Company

13%

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Would you upgrade to more premium versions of IBM InfoSphere DataStage?

My company currently uses the free version of the product, and we are definitely switching to a paid one. We needed a tool that can help us not only integrate our data but use it effectively. For ...

Is IBM InfoSphere DataStage more difficult to use compared to other tools in the field?

I think the tool may cause some difficulties if you have not used other data integration solutions before. I have worked at companies that used different tools for data integration, and they work ...

Do you rely on IBM Cloud Paks for your data? Have you utilized this product, or do you use IBM InfoSphere DataStage without it?

IBM Cloud Paks makes a big difference in your data integration. My company has been using it alongside IBM InfoSphere DataStage and while the main product is good on its own, this one truly expands...

What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

What needs improvement with StreamSets?

We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...

What is your primary use case for StreamSets?

StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...

SSIS vs IBM InfoSphere DataStage

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SSIS vs StreamSets

Compared 7% of the time

webMethods.io Integration vs StreamSets

Compared 6% of the time

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Product Reports

Download IBM InfoSphere DataStage product report

IBM InfoSphere DataStage

June 2024

Download StreamSets product report

May 2024

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IBM

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Overview

IBM InfoSphere DataStage is a high-quality data integration tool that aims to design, develop, and run jobs that move and transform data for organizations of different sizes. The product works by integrating data across multiple systems through a high-performance parallel framework. It supports extended metadata management, enterprise connectivity, and integration of all types of data.

The solution is the data integration component of IBM InfoSphere Information Server, providing a graphical framework for moving data from source systems to target systems. IBM InfoSphere DataStage can deliver data to data warehouses, data marts, operational data sources, and other enterprise applications. The tool works with various types of patterns - extract, transform and load (ETL), and extract, load, and transform (ELT). The scalability of the platform is achieved by using parallel processing and enterprise connectivity.

The solution has various versions, catering to different types of companies, which include the Server Edition, the Enterprise Edition, and the MVS Edition. Depending on which version a company has bought, different goals can be achieved. They include the following:

Designing data flows to extract information from multiple sources, transform the data, and deliver it to target databases or applications.
Delivery of relevant and accurate data through direct connections to enterprise applications.
Reduction of development time and improvement of consistency through prebuilt functions.
Utilization of InfoSphere Information Server tools for accelerating the project delivery cycle.

IBM InfoSphere DataStage can be deployed in various ways, including:

As a service: The tool can be accessed from a subscription model, where its capabilities are a part of IBM DataStage on IBM Cloud Park for Data as a Service. This option offers full management on IBM Cloud.
On premises or in any cloud: The two editions - IBM DataStage Enterprise and IBM DataStage Enterprise Plus - can run workloads on premises or in any cloud when added to IBM DataStage on IBM Cloud Pak for Data as a Service.
On premises: The basic jobs of the tool can be run on premises using IBM DataStage.

IBM InfoSphere DataStage Features

The tool has various features through which users can integrate and utilize their data effectively. The components of IBM InfoSphere DataStage include:

AI services: The tool offers services such as data science, event messaging, data warehousing, and data virtualization. It accelerates processes through artificial intelligence (AI) and offers a connection with IBM Cloud Paks - the cloud-native insight platform of the solution.
Parallel engine: Through this feature, ETL performance can be optimized to process data at scale. This is achieved through parallel engine and load balancing, which maximizes throughput.
Metadata support: This feature of the product uses the IBM Watson Knowledge Catalog to protect companies' sensitive data and monitor who can access it and at what levels.
Automated delivery pipelines: IBM InfoSphere DataStage reduces costs by automating continuous integration and delivery of pipelines.
Prebuilt connectors: The feature for prebuilt connectivity and stages allows users to move data between multiple cloud sources and data warehouses, including IBM native products.
IBM DataStage Flow Designer: This feature offers assistance through machine learning design. The product offers its clients a user-friendly interface which facilitates the work process.
IBM InfoSphere QualityStage: The tool provides a feature that automatically resolves data quality issues and increases the reliability of the delivered data.
Automated failure detection: Through this feature, companies can reduce infrastructure management efforts, relying on the automated detection that the tool offers.
Distributed data processing: Cloud runtimes can be executed remotely through this feature while maintaining its sovereignty and decreasing costs.

IBM InfoSphere DataStage Benefits

This solution offers many benefits for the companies that utilize it for data integration. Some of these benefits include:

Increased speed of workload execution due to better balancing and a parallel engine.
Reduction of data movement costs through integrations and seamless design of jobs.
Modernization of data integration by extending the capabilities of companies' data.
Delivery of reliable data through IBM Cloud Pak for Data.
Utilization of a drag-and-drop interface which assists in the delivery of data without the need for code.
Effective data manipulation allows data to be merged before being mapped and transformed.
Creating easier access of users to their data by providing visual maps of the process and the delivered data.

Reviews from Real Users

A data/solution architect at a computer software company says the product is robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data.

Tirthankar Roy Chowdhury, team leader at Tata Consultancy Services, feels the tool is user-friendly with a lot of functionalities, and doesn't require much coding because of its drag-and-drop features.

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

Sample Customers

Dubai Statistics Center, Etisalat Egypt

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge