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IBM DataStage vs. IBM Watson Studio on Cloud Pak for Data

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM DataStage

    Score8 out of 10
    N/AIBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.N/A

    IBM Watson Studio

    Score10 out of 10
    N/AIBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.N/A
    Pricing
    IBM DataStageIBM Watson Studio
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM DataStageIBM Watson Studio
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    IBM DataStageIBM Watson Studio
    Considered Both Products
    IBM
    Chose IBM DataStage
    DataStage offers better integration capabilities without the need to write code manually. It also has a native ETL engine whereas MSIS requires a SQL Server. It has better integration capabilities with data quality, data profiling and data governance tools. The main drawback of …
    Incentivized
    IBM
    Chose IBM Watson Studio
    We did not use any other one so this would be hard for me to answer.
    Incentivized
    Key User Insights
    Would buy again
    89%
    Would buy again
    8 Answers
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    5 Answers
    No answers on this topic
    Happy with the feature set
    89%
    Happy with the feature set
    8 Answers
    100%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    7 Answers
    No answers on this topic
    Implementation went as expected
    88%
    Implementation went as expected
    7 Answers
    No answers on this topic
    Features
    IBM DataStageIBM Watson Studio
    Data Source Connection
    Comparison of Data Source Connection features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    7.7
    11 Ratings
    8% below category average
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    Connect to traditional data sources7.911 Ratings00 Ratings
    Connecto to Big Data and NoSQL7.610 Ratings00 Ratings
    Data Transformations
    Comparison of Data Transformations features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    7.6
    11 Ratings
    7% below category average
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    Simple transformations8.011 Ratings00 Ratings
    Complex transformations7.311 Ratings00 Ratings
    Data Modeling
    Comparison of Data Modeling features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    7.2
    11 Ratings
    10% below category average
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    Data model creation7.18 Ratings00 Ratings
    Metadata management5.010 Ratings00 Ratings
    Business rules and workflow7.410 Ratings00 Ratings
    Collaboration7.411 Ratings00 Ratings
    Testing and debugging6.711 Ratings00 Ratings
    Data Governance
    Comparison of Data Governance features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    5.3
    10 Ratings
    42% below category average
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    Integration with data quality tools5.310 Ratings00 Ratings
    Integration with MDM tools5.310 Ratings00 Ratings
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    3% below category average
    Connect to Multiple Data Sources00 Ratings8.022 Ratings
    Extend Existing Data Sources00 Ratings8.022 Ratings
    Automatic Data Format Detection00 Ratings10.021 Ratings
    MDM Integration00 Ratings6.414 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    17% above category average
    Visualization00 Ratings10.022 Ratings
    Interactive Data Analysis00 Ratings10.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    15% above category average
    Interactive Data Cleaning and Enrichment00 Ratings10.022 Ratings
    Data Transformations00 Ratings10.021 Ratings
    Data Encryption00 Ratings8.020 Ratings
    Built-in Processors00 Ratings10.021 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    12% above category average
    Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
    Automated Machine Learning00 Ratings10.022 Ratings
    Single platform for multiple model development00 Ratings10.022 Ratings
    Self-Service Model Delivery00 Ratings8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM DataStage and IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM DataStage
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    6% below category average
    Flexible Model Publishing Options00 Ratings9.022 Ratings
    Security, Governance, and Cost Controls00 Ratings7.022 Ratings
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    User Ratings
    IBM DataStageIBM Watson Studio
    Likelihood to Recommend
    5.9
    (11 ratings)
    8.0
    (65 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.2
    (1 ratings)
    Usability
    8.0
    (4 ratings)
    9.6
    (2 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    9.0
    (1 ratings)
    8.2
    (1 ratings)
    Support Rating
    9.6
    (3 ratings)
    8.2
    (1 ratings)
    In-Person Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    7.3
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Vendor post-sale
    -
    (0 ratings)
    7.3
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.2
    (1 ratings)
    User Testimonials
    IBM DataStageIBM Watson Studio
    Likelihood to Recommend
    IBM
    DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.
    Read full review
    IBM
    It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
    Incentivized
    Read full review
    Pros
    IBM
    • Connect to multiple types of data-sources including Oracle, Teradata, Snowflake, SQl Server.
    • Powerful tool to load large volumes of data.
    • Transformation stages allow us to reduce the amount of code needed to create ETL scripts.
    • Allow us to synchronize and refresh data as much as needed.
    Incentivized
    Read full review
    IBM
    • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
    • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
    • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
    • Estimator validation lets data scientists test and prove different models.
    Incentivized
    Read full review
    Cons
    IBM
    • Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
    • Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
    • Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.
    Incentivized
    Read full review
    IBM
    • The cost is steep and so only companies with resources can afford it
    • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
    • It takes a while to learn how to input different kinds of skin defects for detection
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    No answers on this topic
    IBM
    because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
    Incentivized
    Read full review
    Usability
    IBM
    Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
    Incentivized
    Read full review
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    Reliability and Availability
    IBM
    No answers on this topic
    IBM
    From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
    Incentivized
    Read full review
    Performance
    IBM
    It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
    Incentivized
    Read full review
    IBM
    Never had slow response even on our very busy network
    Incentivized
    Read full review
    Support Rating
    IBM
    IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
    Incentivized
    Read full review
    IBM
    I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
    Incentivized
    Read full review
    In-Person Training
    IBM
    No answers on this topic
    IBM
    The trainers on the job are very smart with solutions and very able in teaching
    Incentivized
    Read full review
    Online Training
    IBM
    No answers on this topic
    IBM
    The Platform is very handy and suggests further steps according my previous interests
    Incentivized
    Read full review
    Implementation Rating
    IBM
    No answers on this topic
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    Alternatives Considered
    IBM
    With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.
    Incentivized
    Read full review
    IBM
    The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
    Incentivized
    Read full review
    Scalability
    IBM
    No answers on this topic
    IBM
    It helped us in getting from 0 to DSX without getting lost
    Incentivized
    Read full review
    Return on Investment
    IBM
    • It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
    • Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
    • Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.
    Read full review
    IBM
    • Could instantly show data driven insights to drive 20% incremental revenue over existing results
    • Still don't have a real use case for unstructured data like twitter feed
    • Some of the insights around user actions have driven new projects to automate mundane tasks
    Incentivized
    Read full review
    ScreenShots