We performed a comparison between Elastic Search and IBM Watson Discovery based on real PeerSpot user reviews.
Find out in this report how the two Indexing and Search solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
"The most valuable feature for us is the analytics that we can configure and view using Kibana."
"X-Pack provides good features, like authorization and alerts."
"The most valuable feature is the out of the box Kibana."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"Search is really powerful."
"The search speed is most valuable and important."
"The most valuable feature of the solution is its utility and usefulness."
"Being able to have some rules to extract the entities is valuable. The capability to crawl external sites and internal documents, and then draw internal information with external contents is also valuable."
"The most valuable feature of IBM Watson Discovery is testing, mainly because the product applies conversational AI, which means I can ask questions to get the information I want from a specific test area."
"Language support and the ability to build a natural language of speech recognition are the most valuable features."
"The most valuable features of IBM Watson Discovery are the integration with the rest of the Watson Suite and the Watson Assistant capability. If you use Watson Assistant, the ability for it to be able to determine the accuracy of your voice models and your voice response systems is a benefit."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"The GUI is the part of the program which has the most room for improvement."
"We have an issue with the volume of data that we can handle."
"The UI point of view is not very powerful because it is dependent on Kibana."
"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."
"Elastic Enterprise Search could improve the report templates."
"Elastic Enterprise Search could improve its SSL integration easier. We should not need to go to the back-end servers to do configuration, we should be able to do it on the GUI."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"The pricing is an area for improvement in IBM Watson Discovery because the customer initially used the free version. Still, when he needed more questions and documents, he had to move to a different version, which was paid and cost $500 per month. That change in pricing made my company lose many customers."
"It needs a lot of memory. Our index is very big. It is around 100 gigabytes. So, we need more than 100 gigabytes of memory to use Watson."
"The support from IBM Watson Discovery is good but could improve to make it great."
"There are probably other chatbots out there that were built for specific use cases and are easier to deploy than this. Having said that, Watson is way more flexible. While it may require a greater amount of effort, it is not substantially more than some of the other ones that are kind of prebuilt for a specific use case. It would be good to have more prebuilt and specific use cases and specific business models. It can have better phone integration, even though I think that it is actually becoming less of an issue. Most people are online nowadays."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while IBM Watson Discovery is ranked 2nd in Indexing and Search with 4 reviews. Elastic Search is rated 8.2, while IBM Watson Discovery is rated 7.8. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of IBM Watson Discovery writes "Beneficial accuracy reports, highly scalable, and simple initial setup". Elastic Search is most compared with Faiss, Milvus, Azure Search, Pinecone and Amazon Kendra, whereas IBM Watson Discovery is most compared with Microsoft FAST. See our Elastic Search vs. IBM Watson Discovery report.
See our list of best Indexing and Search vendors.
We monitor all Indexing and Search reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.