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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Db2

    Score8.6 out of 10
    N/ADB2 is a family of relational database software solutions offered by IBM. It includes standard Db2 and Db2 Warehouse editions, either deployable on-cloud, or on-premise.

    $0

    Pytorch

    Score9.4 out of 10
    N/APytorch is an open source machine learning (ML) framework boasting a rich ecosystem of tools and libraries that extend PyTorch and support development in computer vision, NLP and or that supports other ML goals.N/A
    Pricing
    Db2Pytorch
    Editions & Modules
    Db2 on Cloud Lite
    $0
    Db2 on Cloud Standard
    $99
    per month
    Db2 Warehouse on Cloud Flex One
    $898
    per month
    Db2 on Cloud Enterprise
    $946
    per month
    Db2 Warehouse on Cloud Flex for AWS
    2,957
    per month
    Db2 Warehouse on Cloud Flex
    $3,451
    per month
    Db2 Warehouse on Cloud Flex Performance
    13,651
    per month
    Db2 Warehouse on Cloud Flex Performance for AWS
    13,651
    per month
    Db2 Standard Edition
    Contact Sales
    Db2 Advanced Edition
    Contact Sales
    No answers on this topic
    Offerings
    Pricing Offerings
    Db2Pytorch
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional Details——
    More Pricing Information
    Best Alternatives
    Db2Pytorch
    Small Businesses
    Amazon RDS
    Score8.1 out of 10
    TensorFlow
    Score7.6 out of 10
    Medium-sized Companies
    SingleStore
    Score8.2 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    SAP IQ
    Score5.4 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Db2Pytorch
    Likelihood to Recommend
    9.1
    (114 ratings)
    9.0
    (6 ratings)
    Likelihood to Renew
    7.9
    (12 ratings)
    -
    (0 ratings)
    Usability
    8.5
    (9 ratings)
    10.0
    (1 ratings)
    Availability
    9.3
    (64 ratings)
    -
    (0 ratings)
    Performance
    9.1
    (12 ratings)
    -
    (0 ratings)
    Support Rating
    8.9
    (6 ratings)
    -
    (0 ratings)
    In-Person Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    5.6
    (3 ratings)
    -
    (0 ratings)
    Configurability
    9.1
    (2 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    8.0
    (1 ratings)
    -
    (0 ratings)
    Data Sources
    9.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    7.8
    (4 ratings)
    -
    (0 ratings)
    Product Scalability
    8.3
    (66 ratings)
    -
    (0 ratings)
    Vendor post-sale
    9.0
    (2 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    9.0
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Db2Pytorch
    Likelihood to Recommend
    IBM
    I have primarily used it as the basis for a SIS - but I have migrated more than a few systems from there database systems to DB2 (Filemaker, MySQL, etc.). DB2 does have a better structural approach, as opposed to Filemaker, which allows for more data consistency, but this can also lead to an inflexibility that can sometimes be counterintuitive when attempting to compensate for the flexibility of the work environment as Schools tend to have an all in one approach.
    Incentivized
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    Open Source
    They have created Pytorch Lightening on top of Pytorch to make the life of Data Scientists easy so that they can use complex models they need with just a few lines of code, so it's becoming popular. As compared to TensorFlow(Keras), where we can create custom neural networks by just adding layers, it's slightly complicated in Pytorch.
    Incentivized
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    Pros
    IBM
    • While we query a large set of data, the results are generally available within a minute or so.
    • Always reliable - I have never experienced an application going down.
    • It is easy to write queries and find tables and columns.
    • We can log in smoothly without any headaches.
    Incentivized
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    Open Source
    • flexibility
    • Clean code, close to the algorithm.
    • Fast
    • Handles GPUs, multiple GPUs on a single machine, CPUs, and Mac.
    • Versatile, can work efficiently on text/audio/image/tabular datasets.
    Incentivized
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    Cons
    IBM
    • Learning curve for DB resources - Improvements to UI or native command line built-ins can help with increasing efficiencies for DB resources
    • Better resource utilization monitoring and recommendations
    • Continue to adopt support for modern frameworks and languages making it easier for organizations to see making Db2 the easy first choice
    Incentivized
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    Open Source
    • Since pythonic if developing an app with pytorch as backend the response can be substantially slow and support is less compares to Tensorflow
    Incentivized
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    Likelihood to Renew
    IBM
    The DB2 database is a solid option for our school. We have been on this journey now for 3-4 years so we are still adapting to what it can do. We will renew our use of DB2 because we don’t see. Major need to change. Also, changing a main database in a school environment is a major project, so we’ll avoid that if possible.
    Incentivized
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    Open Source
    No answers on this topic
    Usability
    IBM
    You have to be well versed in using the technology, not only from a GUI interface but from a command line interface to successfully use this software to its fullest.
    Incentivized
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    Open Source
    The big advantage of PyTorch is how close it is to the algorithm. Oftentimes, it is easier to read Pytorch code than a given paper directly. I particularly like the object-oriented approach in model definition; it makes things very clean and easy to teach to software engineers.
    Incentivized
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    Reliability and Availability
    IBM
    I have never had DB2 go down unexpectedly. It just works solidly every day. When I look at the logs, sometimes DB2 has figured out there was a need to build an index. Instead of waiting for me to do it, the database automatically created the index for me. At my current company, we have had zero issues for the past 8 years. We have upgrade the server 3 times and upgraded the OS each time and the only thing we saw was that DB2 got better and faster. It is simply amazing.
    Incentivized
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    Open Source
    No answers on this topic
    Performance
    IBM
    The performances are exceptional if you take care to maintain the database. It is a very powerful tool and at the same time very easy to use. In our installation, we expect a DB machine on the mainframe with access to the database through ODBC connectors directly from branch servers, with fabulous end users experience.
    Incentivized
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    Open Source
    No answers on this topic
    Support Rating
    IBM
    Easily the best product support team. :) Whenever we have questions, they have answered those in a timely manner and we like how they go above and beyond to help.
    Incentivized
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    Open Source
    No answers on this topic
    In-Person Training
    IBM
    the material was very clear and all subjects have been handled
    Incentivized
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    Open Source
    No answers on this topic
    Implementation Rating
    IBM
    db2 work well with the application, also the replication tool can keep it up
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    Open Source
    No answers on this topic
    Alternatives Considered
    IBM
    DB2 was more scalable and easily configurable than other products we evaluated and short listed in terms of functionality and pricing. IBM also had a good demo on premise and provided us a sandbox experience to test out and play with the product and DB2 at that time came out better than other similar products.
    Incentivized
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    Open Source
    Pytorch is very, very simple compared to TensorFlow. Simple to install, less dependency issues, and very small learning curve. TensorFlow is very much optimised for robust deployment but very complicated to train simple models and play around with the loss functions. It needs a lot of juggling around with the documentation. The research community also prefers PyTorch, so it becomes easy to find solutions to most of the problems. Keras is very simple and good for learning ML / DL. But when going deep into research or building some product that requires a lot of tweaks and experimentation, Keras is not suitable for that. May be good for proving some hypotheses but not good for rigorous experimentation with complex models.
    Incentivized
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    Scalability
    IBM
    By
    using DB2 only to support my IzPCA activities, my knowledge here
    is somewhat limited.

    Anyway,
    from what I was able to understand, DB2 is extremely scallable.

    Maybe the information below could serve as an example of scalability.
    Customer have an huge mainframe environment, 13x z15 CECs, around
    80 LPARs, and maybe more than 50 Sysplexes (I am not totally sure about this
    last figure...)

    Today
    we have 7 IzPCA
    databases, each one in a distinct Syplex.

    Plans
    are underway to have, at the end, an small LPAR, with only one DB2 sub-system,
    and with only one database, then transmit the data from a lot of other LPARs,
    and then process all the data in this only one database.



    The
    IzPCA collect process (read the data received, manipulate it, and insert rows
    in the tables) today is a huge process, demanding many elapsed
    hours, and lots of CPU.

    Almost
    100% of the tables are PBR type, insert jobs run in parallel, but in 4 of the 7
    database, it is a really a huge and long process.



    Combining
    the INSERTs loads from the 7 databases in only one will be impossible.......,,,,



    But,
    IzPCA recently introduced a new feature, called "Continuous
    Collector"
    .
    By
    using that feature, small amounts of data will be transmited to the central
    LPAR at every 5 minutes (or even less), processed immediately,in
    a short period of time, and with small use of CPU,
    instead of one or two transmissions by day, of very large amounts of data and
    the corresponding collect jobs occurring only once or twice a day, with long
    elapsed times, and huge comsumption of CPU



    I
    suspect the total CPU seconds consumed will be more or less the same in
    both cases, but in the new method it will occur in small bursts
    many times a day!!
    Incentivized
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    Open Source
    No answers on this topic
    Return on Investment
    IBM
    • Negative: Difficult and manual deployment
    • Negative: Missing assistants from common monitoring metrics
    • Positive: Stability
    • Positive: Performance
    • Positive: Resiliency and high availability (HADR)
    • Positive: Data Replication (Q-Rep)
    • Positive: Interaction with storage subsystems for backups (TSM, SVC)
    • Positive: Gigantic monitoring features in the form of table functions
    Incentivized
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    Open Source
    • The ability to make models as never before
    • Being able to control the bias of models was not done before the arrival of Pytorch in our company
    Incentivized
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    ScreenShots

    Db2 Screenshots

    Screenshot of Db2 - Data sharingScreenshot of Db2 - Machine LearningScreenshot of Db2 - Real time insights