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."It gives us the possibility to store and query this data and also do this efficiently and securely and without delays."
"I am impressed with the product's Logstash. The tool is fast and customizable. You can build beautiful dashboards with it. It is useful and reliable."
"It is easy to scale with the cluster node model."
"It's a stable solution and we have not had any issues."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"The AI-based attribute tagging is a valuable feature."
"The solution has great scalability."
"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"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."
"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."
"Language support and the ability to build a natural language of speech recognition are the most valuable features."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"Kibana should be more friendly, especially when building dashboards."
"I would like to see more integration for the solution with different platforms."
"I would rate the stability a seven out of ten. We faced a few issues."
"The one area that can use improvement is the automapping of fields."
"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."
"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."
"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.
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