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Azure AI Search vs. IBM Watson Content Analytics

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure AI Search

    Score8.9 out of 10
    N/AAzure AI Search (formerly Azure Cognitive Search) is enterprise search as a service, from Microsoft.

    $0.10

    Per Hour

    IBM Watson Content Analytics

    Score8.9 out of 10
    N/AIBM Watson Content Analytics is an enterprise search option. This supersedes IBM's older offerings, IBM Omnifind and IBM Content Analytics and Enterprise Search.N/A
    Pricing
    Azure AI SearchIBM Watson Content Analytics
    Editions & Modules
    Basic
    $0.101
    Per Hour
    Standard S1
    $0.336
    Per Hour
    Standard S2
    $1.344
    Per Hour
    Standard S3
    $2.688
    Per Hour
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure AI SearchIBM Watson Content Analytics
    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
    Azure AI SearchIBM Watson Content Analytics
    Small Businesses
    Elasticsearch
    Score8.5 out of 10
    Elasticsearch
    Score8.5 out of 10
    Medium-sized Companies
    Elasticsearch
    Score8.5 out of 10
    Elasticsearch
    Score8.5 out of 10
    Enterprises
    Amazon CloudSearch
    Score8.5 out of 10
    Amazon CloudSearch
    Score8.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure AI SearchIBM Watson Content Analytics
    Likelihood to Recommend
    9.3
    (6 ratings)
    8.0
    (2 ratings)
    Usability
    9.3
    (3 ratings)
    -
    (0 ratings)
    User Testimonials
    Azure AI SearchIBM Watson Content Analytics
    Likelihood to Recommend
    Microsoft
    It's very useful when used with large file systems, once the models index the files good enough, the suggestions are very impressive and produce grounded answers. Since it can natively work with blob storage the requirement for pre-processing the data is eliminated i.e. the data can be searched in its raw form, this makes Azure AI Search a very powerful tool when used with Azure Stack.
    Incentivized
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    IBM
    If one is looking for a content crawling search engine (think "Google" but on your own private system), IBM Watson does a great job. It is also very good for locating duplicate files/folders and lost items. If document organization and searching is the goal, IBM Watson hits the nail on the head.
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    Pros
    Microsoft
    • Incredibly robust back-end infrastructure.
    • Streamlined integration into Microsoft's Azure Cloud.
    • From a user standpoint, it lets the customer easily access their data and provide useful search tips.
    Incentivized
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    IBM
    • Easy Interface - Drag and click based UI.
    • Good amount of tools for visualization.
    • Less amount of time taken to perform analysis.
    Incentivized
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    Cons
    Microsoft
    • Like virtually all Azure services, it has first-class treatment for .Net as the developer platform of choice, but largely ignores other options. While there is a first-party Python SDK, there are only community packages for other languages like Ruby and Node. Might be a game of roulette for those to be kept up-to-date. This might make it a non-starter for some teams that don't want to do the work to integrate with the REST API directly.
    • In my opinion, partitions inside of Azure Search don't count as data segregation for customers in a multi-tenant app, so any application where you have many customers with high-security concerns, Azure Search is probably a non-starter.
    • To elaborate on the multi-tenant issue: Azure Search's approach to pricing is pretty steep. While there is a free tier for small applications (50MB of content or less) the first paid tier is about 14x more expensive than the first SQL Database tier that supports full-text search. For many applications, it makes a lot more economic sense to just run some LIKE or CONTAINS queries on columns in a table rather than going with Azure Search.
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    IBM
    • The software is semi-limited to indexing and searching.
    • Software does not force a specific "structure" as some document management systems do.
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    Usability
    Microsoft
    I give 10 rating because by using this endpoint and api key only we able to build that chatbot product in a timeline given by our client and also creating the endpoint and keys from the portal is also very easy for Azure AI Search and it doesn't take much time and also scalability is good.
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    IBM
    No answers on this topic
    Alternatives Considered
    Microsoft
    It is good for me, and I want to rate this product 9/10. I hope they continue to improve and also offer a free plan with more benefits to learn Azure AI Search.
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    IBM
    IBM Watson is not quite in the same category as Worldox or NetDocuments as both are full-fledged document management. However, both vendors provide a similar searching and indexing product. Worldox provides searching and indexing but the Indexer is somewhat prone to issues. IBM Watson does not have the stability/consistency issues. NetDocuments is cloud-hosted document management and its index does not seem to have issues. That being said, there is a large premium as the data is all stored in a cloud container with the management system.
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    Return on Investment
    Microsoft
    • When integrated with our existing file system the Azure AI Search helped users tremendously by reducing search times and improve efficacy of intended result.
    • Since Azure AI Search is a PaaS solution, we had very short ideation to go-live timespan, which ended up reflecting in our product performance.
    • A rare but not negligible occurrence was correctness of search being questionable when new data was added to the system. The search returns false positive results.
    Incentivized
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    IBM
    • It has provided a positive work environment.
    • Since its easy and understandable good amount of team communication improved.
    Incentivized
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