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IBM Watson Studio on Cloud Pak for Data vs. Amazon Redshift

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    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

    Amazon Redshift

    Score8.9 out of 10
    N/AAmazon Redshift is a hosted data warehouse solution, from Amazon Web Services.

    $0.24

    per GB per month

    Pricing
    IBM Watson StudioAmazon Redshift
    Editions & Modules
    No answers on this topic
    Redshift Managed Storage
    $0.24
    per GB per month
    Current Generation
    $0.25 - $13.04
    per hour
    Previous Generation
    $0.25 - $4.08
    per hour
    Redshift Spectrum
    $5.00
    per terabyte of data scanned
    Offerings
    Pricing Offerings
    IBM Watson StudioAmazon Redshift
    Free Trial
    NoNo
    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 Watson StudioAmazon Redshift
    Considered Both Products
    IBM
    No answer on this topic
    Amazon AWS
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    78%
    Would buy again
    14 Answers
    Delivers good value for the price
    No answers on this topic
    82%
    Delivers good value for the price
    14 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    78%
    Happy with the feature set
    14 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    93%
    Lived up to sales and marketing promises
    14 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    16 Answers
    Features
    IBM Watson StudioAmazon Redshift
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM Watson Studio on Cloud Pak for Data and Amazon Redshift
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    3% below category average
    Amazon Redshift
    -
    Ratings
    Connect to Multiple Data Sources8.022 Ratings00 Ratings
    Extend Existing Data Sources8.022 Ratings00 Ratings
    Automatic Data Format Detection10.021 Ratings00 Ratings
    MDM Integration6.414 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM Watson Studio on Cloud Pak for Data and Amazon Redshift
    Feature
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    17% above category average
    Amazon Redshift
    -
    Ratings
    Visualization10.022 Ratings00 Ratings
    Interactive Data Analysis10.022 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM Watson Studio on Cloud Pak for Data and Amazon Redshift
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    15% above category average
    Amazon Redshift
    -
    Ratings
    Interactive Data Cleaning and Enrichment10.022 Ratings00 Ratings
    Data Transformations10.021 Ratings00 Ratings
    Data Encryption8.020 Ratings00 Ratings
    Built-in Processors10.021 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM Watson Studio on Cloud Pak for Data and Amazon Redshift
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    12% above category average
    Amazon Redshift
    -
    Ratings
    Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
    Automated Machine Learning10.022 Ratings00 Ratings
    Single platform for multiple model development10.022 Ratings00 Ratings
    Self-Service Model Delivery8.020 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM Watson Studio on Cloud Pak for Data and Amazon Redshift
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    6% below category average
    Amazon Redshift
    -
    Ratings
    Flexible Model Publishing Options9.022 Ratings00 Ratings
    Security, Governance, and Cost Controls7.022 Ratings00 Ratings
    Best Alternatives
    IBM Watson StudioAmazon Redshift
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    No answers on this topic
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Snowflake
    Score8.7 out of 10
    Enterprises
    Posit
    Score10 out of 10
    Snowflake
    Score8.7 out of 10
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    User Ratings
    IBM Watson StudioAmazon Redshift
    Likelihood to Recommend
    8.0
    (65 ratings)
    9.0
    (38 ratings)
    Likelihood to Renew
    8.2
    (1 ratings)
    -
    (0 ratings)
    Usability
    9.6
    (2 ratings)
    9.0
    (10 ratings)
    Availability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Performance
    8.2
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    8.2
    (1 ratings)
    9.0
    (7 ratings)
    In-Person Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Online Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    7.3
    (1 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    10.0
    (1 ratings)
    Product Scalability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    7.3
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    8.2
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM Watson StudioAmazon Redshift
    Likelihood to Recommend
    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
    Amazon AWS
    If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
    Incentivized
    Read full review
    Pros
    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
    Amazon AWS
    • [Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results.
    • [Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases
    • [Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store.
    • [Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance.
    Incentivized
    Read full review
    Cons
    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
    Amazon AWS
    • We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
    • Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
    • Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
    Incentivized
    Read full review
    Amazon AWS
    No answers on this topic
    Usability
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    Amazon AWS
    Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
    Incentivized
    Read full review
    Reliability and Availability
    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
    Amazon AWS
    No answers on this topic
    Performance
    IBM
    Never had slow response even on our very busy network
    Incentivized
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    Amazon AWS
    No answers on this topic
    Support Rating
    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
    Amazon AWS
    The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
    Incentivized
    Read full review
    In-Person Training
    IBM
    The trainers on the job are very smart with solutions and very able in teaching
    Incentivized
    Read full review
    Amazon AWS
    No answers on this topic
    Online Training
    IBM
    The Platform is very handy and suggests further steps according my previous interests
    Incentivized
    Read full review
    Amazon AWS
    No answers on this topic
    Implementation Rating
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    Amazon AWS
    No answers on this topic
    Alternatives Considered
    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
    Amazon AWS
    Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
    Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
    Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
    Incentivized
    Read full review
    Contract Terms and Pricing Model
    IBM
    No answers on this topic
    Amazon AWS
    Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.
    Incentivized
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    Scalability
    IBM
    It helped us in getting from 0 to DSX without getting lost
    Incentivized
    Read full review
    Amazon AWS
    No answers on this topic
    Return on Investment
    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
    Amazon AWS
    • Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost.
    • Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time.
    • Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift.
    Incentivized
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    ScreenShots