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Elastic Search vs IBM Watson Discovery comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Elastic Search
Ranking in Indexing and Search
1st
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
65
Ranking in other categories
Cloud Data Integration (11th), Search as a Service (1st), Vector Databases (1st)
IBM Watson Discovery
Ranking in Indexing and Search
3rd
Average Rating
7.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Indexing and Search category, the mindshare of Elastic Search is 28.0%, up from 24.6% compared to the previous year. The mindshare of IBM Watson Discovery is 3.7%, down from 6.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search
 

Featured Reviews

Saurav Kumar - PeerSpot reviewer
Provides us with the capability to execute multiple queries according to our requirements
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical.
Geraldo Lima - PeerSpot reviewer
Stable, scalable, and has testing and conversational AI features
The total time it takes to deploy IBM Watson Discovery depends on the documents you'll be working with. For example, I was in a situation where I was working with some painting files and folders for a painting store. The store had PDF documents, but the information was mixed up, so I had to treat the documents on IBM Watson Discovery, and discovering and understanding each PDF file took longer. The process is more straightforward for plain documents, and you have to work with questions that will help IBM Watson Discovery understand the documents. The time to deploy the product depends on the quantity and type of documents you'll be working with.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"The search speed is most valuable and important."
"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."
"It's a stable solution and we have not had any issues."
"Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana."
"The most valuable features are the detection and correlation features."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"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 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."
"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."
 

Cons

"We have an issue with the volume of data that we can handle."
"The metadata gets stored along with indexes and isn't queryable."
"Machine learning on search needs improvement."
"The UI point of view is not very powerful because it is dependent on Kibana."
"Dashboards could be more flexible, and it would be nice to provide more drill-down capabilities."
"New Relic could be more flexible, similar to Elasticsearch."
"There is an index issue in which the data starts to crash as it increases."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"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."
 

Pricing and Cost Advice

"It can be expensive."
"The solution is free."
"We are using the free open-sourced version of this solution."
"An X-Pack license is more affordable than Splunk."
"we are using a licensed version of the product."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"​The pricing and license model are clear: node-based model."
"The solution is affordable."
"Cost-wise, it is very reasonable because it is cloud-based."
"IBM Watson Discovery is an expensive product."
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
15%
Manufacturing Company
9%
Government
7%
Computer Software Company
24%
Government
16%
Financial Services Firm
14%
University
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
I am not directly involved with pricing or setup costs. While I know a portion is open-source, a paid version might be necessary.
What needs improvement with ELK Elasticsearch?
An improvement would be to have an interface that allows easier navigation and tracing of logs. The current system requires manually inputting dates to verify alerts. A visual timeline that pinpoin...
What do you like most about IBM Watson Discovery?
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 tes...
What needs improvement with IBM Watson Discovery?
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 differen...
 

Comparisons

No data available
 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Learn More

Video not available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
Prudential, Bradesco, Woodside
Find out what your peers are saying about Elastic Search vs. IBM Watson Discovery and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.