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BA Insight vs Elastic Search comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

BA Insight
Ranking in Indexing and Search
19th
Average Rating
8.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Elastic Search
Ranking in Indexing and Search
1st
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
99
Ranking in other categories
Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (5th)
 

Mindshare comparison

As of June 2026, in the Indexing and Search category, the mindshare of BA Insight is 2.6%, up from 0.8% compared to the previous year. The mindshare of Elastic Search is 10.1%, down from 24.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search Mindshare Distribution
ProductMindshare (%)
Elastic Search10.1%
BA Insight2.6%
Other87.3%
Indexing and Search
 

Featured Reviews

it_user265773 - PeerSpot reviewer
GDS Search Services Leader, Knowledge Services at a financial services firm with 10,001+ employees
Refiners help to easily narrow down results based on metadata applied to content. Previews allow users to take action from search results without opening the document.
The preview feature made the results page take too long to load. It also took a long time to generate document previews. Randomly, it would show “cannot load preview”. I do not know the reason, but that happened a lot and we had to turn this feature off. Preview load time could be reduced. We saw that it takes forever to load a document preview, and at times, after waiting, it just gave a ‘cannot load preview error’.
reviewer2817942 - PeerSpot reviewer
Senior Software Engineer at a consultancy with 11-50 employees
Logging and vector search have transformed observability and empowered reliable ai agents
Elastic Search is not specifically being used for certain purposes. I deploy Elastic Search database on the cloud and use cloud services so that nobody can attack. However, I do not use Elastic Search to resolve attack issues. The basic main purpose of Elastic Search, as of now, I feel it can do more in the AI area. Sometime I saw that when I am developing RAG and have to generate the embeddings, which I call metadata, sometimes it tries to fail. That durability or issue handling should be improved, but apart from that, I did not find anything as of now. As per my use case, whatever I am using seems pretty good. Apart from that, some definitely improvement will be there. One improvement is that it should be faster. Whenever I am searching any logs, it takes much time. For example, if I open my log in Notepad or a similar tool, I can search the text within a second. With Elastic Search, it takes a little bit of time, ten to fifteen seconds. That can be improved. Sometimes, engineers take time to assign when I create a ticket.

Quotes from Members

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

Pros

"Refiners help to easily narrow down results based on metadata applied to content, and the preview feature helps users to take action from the search results page without opening the documents."
"Elastic Search has impacted my organization positively as we use it for logging and APM."
"The solution is quite scalable and this is one of its advantages."
"The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"The positive impact I've seen from using Elastic Search includes replacing conventional databases and being able to store much more unstructured data."
"Elasticsearch includes a graphical user interface (GUI) called Kibana, and the GUI features are extremely beneficial to us."
"The machine learning features of Elastic Search are very interesting, including the possibility to include models such as ELSER and different multilingual models that let us fine-tune our searches and use them in our search projects."
 

Cons

"The preview feature made the results page take too long to load."
"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"The real-time search functionality is not operational due to its impact on system resources."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"Could have more open source tools and testing."
"Scalability and ROI are the areas they have to improve."
 

Pricing and Cost Advice

Information not available
"We are using the open-sourced version."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"The tool is an open-source product."
"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
"The pricing structure depends on the scalability steps."
"we are using a licensed version of the product."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"The solution is free."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Manufacturing Company
9%
Computer Software Company
8%
Retailer
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise49
 

Questions from the Community

Ask a question
Earn 20 points
What is your experience regarding pricing and costs for ELK Elasticsearch?
Elastic Search is easy to use in Azure cloud. Mostly, my full company uses Azure cloud, so it is easy to use. Cost-wise, my company found Elastic Search is good. Cost matters. Based on cost and use...
What needs improvement with ELK Elasticsearch?
The initial configuration could be easier; at first, the learning curve is a little high, and over time, it becomes easier. For me, the initial configuration might be improved.
What is your primary use case for ELK Elasticsearch?
We use Elastic Search for a research application based on paper study, and the primary usage is for indexing the data and then functioning in a similar way to an e-commerce search bar.
 

Comparisons

 

Also Known As

BA Insight Enterprise Search Essentials, BA Insight Enterprise Search
Elastic Enterprise Search, Swiftype, Elastic Cloud
 

Overview

 

Sample Customers

AARP, Amgen, Blank Rome, Chevron, Australian Government, EY, Hogan Lovells, Keurig Green Mountain, OFWAT, Pfizer, Stanford University, US Army, White & Case
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.
Find out what your peers are saying about Elastic, Glean, Coveo and others in Indexing and Search. Updated: June 2026.
900,838 professionals have used our research since 2012.