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IBM InfoSphere DataStage vs SAS Data Management comparison

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Buyer's Guide
IBM InfoSphere DataStage vs. SAS Data Management
July 2022
Find out what your peers are saying about IBM InfoSphere DataStage vs. SAS Data Management and other solutions. Updated: July 2022.
620,068 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes.""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.""In StreamSets, everything is in one place.""It is really easy to set up and the interface is easy to use.""I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."

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"Offers great flexibility.""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.""Once you have Infosphere up and running properly, it is stable.""The Hierarchical Data Stage is good.""It is quite useful and powerful.""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.""It's a robust solution.""The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"

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"The tool is reliable, quick, and powerful.""The technical support is excellent.""Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools.""The product offers very good flexibility.""In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."

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Cons
"We've seen a couple of cases where it appears to have a memory leak or a similar problem.""If you use JDBC Lookup, for example, it generally takes a long time to process data.""The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time.""We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back.""Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."

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"Currently lacking virtualization ability.""The response time from support is slow and needs to be improved.""The pricing should be lower.""The initial setup could be more straightforward.""In the future, I would like to see more integration with cloud technologies.""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.""The setup is extremely difficult.""It would be useful to provide support for Python, AR, and Java."

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"The solution could use better documentation.""With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process.""One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place.""We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows.""The solution is quite expensive and hard to install/configure."

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Pricing and Cost Advice
  • "We are running the community version right now, which can be used free of charge."
  • "StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."
  • "It has a CPU core-based licensing, which works for us and is quite good."
  • "There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."
  • More StreamSets Pricing and Cost Advice →

  • "The cost is too high."
  • "It's very expensive."
  • "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 price is expensive but there are no licensing fees."
  • "It is quite expensive."
  • "It's quite expensive."
  • More IBM InfoSphere DataStage Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:It is really easy to set up and the interface is easy to use.
    Top Answer:We've seen a couple of cases where it appears to have a memory leak or a similar problem. It grows for a bit and then… more »
    Top Answer:We typically use it to transport our Oracle raw datasets up to Microsoft Azure, and then into SQL databases there.
    Top Answer:The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms
    Top Answer:Comparable solutions will have common disadvantages, which is the total cost of the project. It's quite expensive.
    Top Answer: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… more »
    Top Answer:The tool is reliable, quick, and powerful.
    Top Answer:The solution is quite expensive and hard to install/configure.
    Comparisons
    Also Known As
    SAS Data Management Platform, Data Management Platform, DataFlux
    Learn More
    StreamSets
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    Overview

    StreamSets offers an end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power the modern data ecosystem and hybrid integration.

    Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps.

    With StreamSets, you can deliver the continuous data that drives the connected enterprise.

    IBM InfoSphere DataStage integrates data across multiple systems using a high performance parallel framework, and it supports extended metadata management and enterprise connectivity. The scalable platform provides more flexible integration of all types of data, including big data at rest (Hadoop-based) or in motion (stream-based), on distributed and mainframe platforms.

    Every decision, every business move, every successful customer interaction - they all come down to high-quality, well-integrated data. If you don't have it, you don't win. SAS Data Management is an industry-leading solution built on a data quality platform that helps you improve, integrate and govern your data.

    Offer
    Learn more about StreamSets
    Learn more about IBM InfoSphere DataStage
    Learn more about SAS Data Management
    Sample Customers
    Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
    Dubai Statistics Center, Etisalat Egypt
    Data Management, 1-800-FLOWERS.COM, Absa, Aegon, Allianz Global Corporate & SpecialtyAusgrid, Bank of Queensland, Bell, BMC Software, Canada Post, Ceska pojistovna, Chantecler, Chubb Group of Insurance Companies, Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Enerjisa, ERGO Insurance Group, Florida Department of Corrections, Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, North Carolina Office of Information Technology Services, Orlando Magic, OTP Group, PITT OHIO, Plano Independent School District, RWE Poland, Spanish Air Force, Stockholm County Council, Telus, The Travel Corporation, Transitions Optical, Triad Analytic Solutions, UNIQA, US Census Bureau, US Department of Housing and Urban Development, USDA National Agricultural Statistics Service, West Midlands Police, XS Inc., Zenith Insurance
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company18%
    Comms Service Provider14%
    Financial Services Firm13%
    Insurance Company8%
    REVIEWERS
    Computer Software Company67%
    Aerospace/Defense Firm11%
    Healthcare Company11%
    Financial Services Firm11%
    VISITORS READING REVIEWS
    Computer Software Company23%
    Financial Services Firm15%
    Comms Service Provider14%
    Insurance Company6%
    VISITORS READING REVIEWS
    Computer Software Company32%
    Comms Service Provider11%
    Financial Services Firm9%
    Government8%
    Company Size
    VISITORS READING REVIEWS
    Small Business14%
    Midsize Enterprise13%
    Large Enterprise72%
    REVIEWERS
    Small Business43%
    Midsize Enterprise4%
    Large Enterprise54%
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise13%
    Large Enterprise74%
    REVIEWERS
    Small Business46%
    Midsize Enterprise8%
    Large Enterprise46%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise8%
    Large Enterprise72%
    Buyer's Guide
    IBM InfoSphere DataStage vs. SAS Data Management
    July 2022
    Find out what your peers are saying about IBM InfoSphere DataStage vs. SAS Data Management and other solutions. Updated: July 2022.
    620,068 professionals have used our research since 2012.

    IBM InfoSphere DataStage is ranked 9th in Data Integration Tools with 9 reviews while SAS Data Management is ranked 15th in Data Integration Tools with 5 reviews. IBM InfoSphere DataStage is rated 7.6, while SAS Data Management is rated 7.8. The top reviewer of IBM InfoSphere DataStage writes "Robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data". On the other hand, the top reviewer of SAS Data Management writes "One-stop-shop solution for sorting, categorizing and summarizing your data". IBM InfoSphere DataStage is most compared with SSIS, Talend Open Studio, AWS Glue, Informatica PowerCenter and Azure Data Factory, whereas SAS Data Management is most compared with Informatica PowerCenter, Informatica Axon, Collibra Governance, Microsoft Purview and Palantir Gotham. See our IBM InfoSphere DataStage vs. SAS Data Management report.

    See our list of best Data Integration Tools vendors and best Cloud Data Integration vendors.

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