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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
18th
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
90
Ranking in other categories
Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
 

Mindshare comparison

As of March 2026, in the Indexing and Search category, the mindshare of BA Insight is 2.7%, up from 1.0% compared to the previous year. The mindshare of Elastic Search is 12.0%, down from 26.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search Mindshare Distribution
ProductMindshare (%)
Elastic Search12.0%
BA Insight2.7%
Other85.3%
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’.
Anurag Pal - PeerSpot reviewer
Technical Lead at a consultancy with 10,001+ employees
Search and aggregations have transformed how I manage and visualize complex real estate data
Elastic Search consumes lots of memory. You have to provide the heap size a lot if you want the best out of it. The major problem is when a company wants to use Elastic Search but it is at a startup stage. At a startup stage, there is a lot of funds to consider. However, their use case is that they have to use a pretty significant amount of data. For that, it is very expensive. For example, if you take OLTP-based databases in the current scenario, such as ClickHouse or Iceberg, you can do it on 4GB RAM also. Elastic Search is for analytical records. You have to do the analytics on it. According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive. Another thing is that there is an open source available for that, such as ClickHouse. Around 2014 and 2012, there was only one competitor at that time, which was Solr. But now, not only is Solr there, but you can take ClickHouse and you have Iceberg also. How are we going to compete with them? There is also a fork of Elastic Search that is OpenSearch. As far as I have seen in lots of articles I am reading, users are using it as the ELK stack for logs and analyzing logs. That is not the exact use case. It can do more than that if used correctly. But as it involves lots of cost, people are shifting from Elastic Search to other sources. When I am talking about pricing, it is not only the server pricing. It is the amount of memory it is using. The pricing is basically the heap Java, which is taking memory. That is the major problem happening here. If we have to run an MVP, a client comes to me and says, "Anurag, we need to do a proof of concept. Can we do it if I can pay a 4GB or 16GB expense?" How can I suggest to them that a minimum of 16GB is needed for Elastic Search so that your proof of concept will be proved? In that case, what I have to suggest from the beginning is to go with Cassandra or at the initial stage, go with PostgreSQL. The problem is the memory it is taking. That is the only thing.

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."
"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."
"The most valuable feature of the solution is its utility and usefulness."
"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."
"From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs."
"The most valuable feature is the out of the box Kibana."
"I value the feature that allows me to share dashboards with different people with different levels of access."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"The stability of Elasticsearch was very high, and I would rate it a ten."
 

Cons

"The preview feature made the results page take too long to load."
"The setup is somewhat complicated due to multiple dependencies and relations with different systems."
"An improvement would be to have an interface that allows easier navigation and tracing of logs."
"I think the biggest issue we had with Elastic Search was regarding integrations with our multi-factor authentication tool."
"More AI would be beneficial. I would also appreciate more simplicity in dashboards."
"Elastic needs to work on their Machine Learning offering because currently they have been trying to make it a black box which doesn't work for a serious user (a Data Scientist) as it doesn't give any control over the underlying algorithm."
"Elastic Enterprise Search's tech support is good but it could be improved."
"The metadata gets stored along with indexes and isn't queryable."
"There is a maximum of 10,000 entries, so the limitation means that if I wanted to analyze certain IP addresses more than 10,000 times, I wouldn't be able to dump or print that information."
 

Pricing and Cost Advice

Information not available
"We use the free version for some logs, but not extensive use."
"An X-Pack license is more affordable than Splunk."
"We are using the free open-sourced version of this solution."
"The solution is free."
"We are using the free version and intend to upgrade."
"​The pricing and license model are clear: node-based model."
"To access all the features available you require both the open source license and the production license."
"The price could be better."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
10%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business38
Midsize Enterprise10
Large Enterprise45
 

Questions from the Community

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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?
On the subject of pricing, Elastic Search is very cost-efficient. You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
What needs improvement with ELK Elasticsearch?
From the UI point of view, we are using most probably Kibana, and I think they can do much better than that. That is something they can fine-tune a little bit, and then it will definitely be a good...
 

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, Luigi's Box, OpenText and others in Indexing and Search. Updated: February 2026.
884,933 professionals have used our research since 2012.