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Amazon CloudSearch vs. IBM Watson Explorer

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Amazon CloudSearch

    Score9 out of 10
    N/AAmazon CloudSearch is enterprise search as a service, from Amazon Web Services.N/A

    IBM Watson Explorer

    Score8.4 out of 10
    N/AIBM Watson Explorer supports enterprise search with unstructured data analysis, machine learning, and content analysis to improve decision-making, support customer service or serve other business needs.N/A
    Pricing
    Amazon CloudSearchIBM Watson Explorer
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Amazon CloudSearchIBM Watson Explorer
    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
    Best Alternatives
    Amazon CloudSearchIBM Watson Explorer
    Small Businesses
    Elasticsearch
    Score8.6 out of 10
    Elasticsearch
    Score8.6 out of 10
    Medium-sized Companies
    Algolia
    Score8.7 out of 10
    Algolia
    Score8.7 out of 10
    Enterprises
    Algolia
    Score8.7 out of 10
    Algolia
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Amazon CloudSearchIBM Watson Explorer
    Likelihood to Recommend
    7.0
    (1 ratings)
    9.0
    (1 ratings)
    User Testimonials
    Amazon CloudSearchIBM Watson Explorer
    Likelihood to Recommend
    Amazon AWS
    Amazon Cloudsearch can be suitable for some queries that require fast data. For example, in our case, we used CloudSearch, in a tool called Global Search. That will search everything like names, emails and a lot of stuff in our application. If you want fast data and you have a simple query, Global Search isn't appropriate for you.
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    IBM
    The Watson Explorer is great because it potentially replaces a meriad of other low-level analytics products that we would need to use for data analytics and data mining. WEX isn't really suitable much beyond doing text and data analytics and performing machine learning, so if your team doesn't really have a use-case that fits all of these categories, it is worth looking at an alternative.
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    Pros
    Amazon AWS
    • Really fast queries
    • Good Reporting
    • Reduce the cost of the server
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    IBM
    • Free to try - It's possible to use most of the useful features of Watson Explore on their trial/demo accounts.
    • Super well-designed data analytics tool - Most of the tools and features of the explorer are really useful, and truly help you fully understand the depth of any format of textual data.
    • Extensive sources compatibility - WEX can retrieve data from a large range of sources, and the compatibility there is quite good as well.
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    Cons
    Amazon AWS
    • Can take some time to implement
    • The initial configuration can be tricky
    • Takes some time to update the values
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    IBM
    • Support is just OK, like most of the other IBM Watson products. The setup/integration is really hands-on, but it's also problematic because support later may take a considerable amount of time.
    • UI could still use a little more improvement - part of the administration and sources dashboards are hard to navigate.
    • The Application Builder is a great part of the product, but hard to learn/understand - this is where we needed the most support from IBM and tutorials/documentation.
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    Alternatives Considered
    Amazon AWS
    I didn't investigate the best alternatives to CloudSearch, but did help with implementing this feature in our application. But from what i tested and used - Cloudsearch is very fast to get queries. Some negative points can be the time to implement this and some configurations that can be tricky.
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    IBM
    Google Cloud offers a Natural Language product, but it is just an API. This API doesn't offer the useful visualizations of relations, analytics, and graphs that IBM Watson Explorer offers on their interface. For this reason, we chose to go with IBM WEX. For later stages of our production, we decided to use Google's NLP API because we found that it was quick to integrate into production after studying data and developing models using IBM WEX.
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    Return on Investment
    Amazon AWS
    • Positive Point - Reduced the server load
    • Negative point - Not suitable for all queries
    • Negative Point - Time to implement this feature
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    IBM
    • Positive - Trial/demo period. This was really useful for us to figure out what features of WEX we liked most and how difficult it would be to integrate WEX into our workflow.
    • Negative - On-boarding was long and almost always requires support from IBM support, unlike most other products this advanced.
    • Positive - WEX replaced a large selection of alternative products we would have to use for the same functionality, and having all of that function in one place was definitely helpful.
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    ScreenShots