Apache Solr vs. IBM Watson Explorer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Solr
Score 6.8 out of 10
N/A
Apache Solr is an open-source enterprise search server.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
Apache SolrIBM Watson Explorer
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SolrIBM 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
Apache SolrIBM Watson Explorer
Small Businesses
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Medium-sized Companies
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Score 8.9 out of 10
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Score 8.9 out of 10
Enterprises
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User Ratings
Apache SolrIBM Watson Explorer
Likelihood to Recommend
9.0
(10 ratings)
9.0
(1 ratings)
User Testimonials
Apache SolrIBM Watson Explorer
Likelihood to Recommend
Apache
Solr spins up nicely and works effectively for small enterprise environments providing helpful mechanisms for fuzzy searches and facetted searching. For larger enterprises with complex business solutions you'll find the need to hire an expert Solr engineer to optimize the powerful platform to your needs. Internationalization is tricky with Solr and many hosting solutions may limit you to a latin character set.
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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
Apache
  • Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
  • Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
  • Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.
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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
Apache
  • These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
  • We have lot of classifications and lot of data for each classification. This gave us several problems:
  • First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
  • Second: We needed several load balanced Solr databases.
  • Third: We needed to update all the databases and keep old data status.
  • If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.
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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
Apache
Apache Solr is a ready-to-use product addressing specific use cases such as keyword searches from a huge set of data documents.
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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
Apache
  • Improved response time in e-commerce websites.
  • Developer's job is easier with Apache Solr in use.
  • Customization in filtering and sorting is possible.
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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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