Amazon CloudSearch vs. IBM Watson Explorer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon CloudSearch
Score 7.7 out of 10
N/A
Amazon CloudSearch is enterprise search as a service, from Amazon Web Services.N/A
IBM Watson Explorer
Score 8.4 out of 10
N/A
IBM 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
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Medium-sized Companies
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Enterprises
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User Ratings
Amazon CloudSearchIBM Watson Explorer
Likelihood to Recommend
6.0
(2 ratings)
9.0
(1 ratings)
User Testimonials
Amazon CloudSearchIBM Watson Explorer
Likelihood to Recommend
Amazon AWS
I would like to mentioned about the scenario where Amazon cloud search was well suited is when we need regular updation of data and the subject matter requires continuous alterations due to the continuous changing environment and talking abut the least appropriate would the times when their is high level of customisation requirements in the project.
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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
  • First thing I would like to mentioned about its indexing speed, I have noticed while working with large sums of data
  • Second I would like to mentioned about customisation challenge, although it is also its pros but a con as well, as it is a tedious task to customise when time value comes place as well.
  • Thirdly, I do feel that its advanced search queries could be more supported. I have seen some level of lagging when it comes to more advanced search queries given the size of data.
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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
  • It has directly or indirectly improved the operational effiecncy for sure.
  • Its limitations towards limited customisation requirements makes it a bit negative side of the scenario.
  • Its scalability of the growth offers seamless accommodation of large data sets which is a positive impact although.
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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