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ChatGPT vs Elastic Search comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jun 5, 2025

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

ChatGPT
Average Rating
8.4
Reviews Sentiment
8.2
Number of Reviews
3
Ranking in other categories
AI Writing Tools (4th), AI Code Assistants (6th), Large Language Models (LLMs) (4th), AI Proofreading Tools (3rd)
Elastic Search
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
71
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st), Vector Databases (3rd)
 

Mindshare comparison

ChatGPT and Elastic Search aren’t in the same category and serve different purposes. ChatGPT is designed for Large Language Models (LLMs) and holds a mindshare of 6.2%, up 5.0% compared to last year.
Elastic Search, on the other hand, focuses on Indexing and Search, holds 23.7% mindshare, down 27.2% since last year.
Large Language Models (LLMs)
Indexing and Search
 

Featured Reviews

Malte Landwehr - PeerSpot reviewer
Using technology helps streamline research, improve writing skills, and brainstorm creative ideas
I don't have one use case. I have many. I use ChatGPT for creativity and brainstorming. I often use it to generate ten or twenty ideas for a topic, and that often helps me to then pick which direction I actually want to go into. I use it to fine-tune my writing skills. When I write an important…
Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.

Quotes from Members

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

Pros

"The initial setup was very simple."
"I would rate ChatGPT a nine on a scale of one to ten."
"Rockset is very fast, and you can query just like in MySQL."
"Gives us a more user-friendly, centralized solution (for those who just needed a quick glance, without being masters of sed and awk) as well as the ability to implement various mechanisms for machine-learning from our logs, and sending alerts for anomalies."
"The most valuable feature of Elastic Enterprise Search is the opportunity to search behind and between different logs."
"It is easy to scale with the cluster node model.​"
"Elastic Search is very quick when handling a large volume of data."
"I appreciate that Elastic Enterprise Search is easy to use and that we have people on our team who are able to manage it effectively."
"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"Search is really powerful."
 

Cons

"Rockset is now bought by OpenAI. It’s uncertain if Rockset will continue to exist as it is."
"Filtering the database based on indexes is difficult in Rockset and should be simplified."
"We'd like more user-friendly integrations."
"Elasticsearch could be improved in terms of scalability."
"The real-time search functionality is not operational due to its impact on system resources."
"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."
"Ratio aggregation is not supported in this solution."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"New Relic could be more flexible, similar to Elasticsearch."
"The reports could improve."
 

Pricing and Cost Advice

Information not available
"The price of Elastic Enterprise is very, very competitive."
"The solution is less expensive than Stackdriver and Grafana."
"We are using the open-sourced version."
"The premium license is expensive."
"The tool is not expensive. Its licensing costs are yearly."
"The solution is affordable."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"The tool is an open-source product."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Manufacturing Company
9%
Comms Service Provider
8%
Energy/Utilities Company
8%
Computer Software Company
16%
Financial Services Firm
15%
Government
9%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What needs improvement with ChatGPT?
I think it's pretty good. No recommendations.
What is your primary use case for ChatGPT?
I don't have one use case. I have many. I use ChatGPT for creativity and brainstorming. I often use it to generate ten or twenty ideas for a topic, and that often helps me to then pick which direct...
What advice do you have for others considering ChatGPT?
Just use it. Just don't be afraid to use it. Just go with it. I would rate ChatGPT a nine on a scale of one to ten. It's really, really good.
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?
We used the open-source version of Elasticsearch, which was free.
What needs improvement with ELK Elasticsearch?
It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already...
 

Comparisons

 

Also Known As

Rockset
Elastic Enterprise Search, Swiftype, Elastic Cloud
 

Overview

 

Sample Customers

1. Adobe 2. Cisco 3. Comcast 4. DoorDash 5. Expedia 6. Facebook 7. GitHub 8. IBM 9. Lyft 10. Microsoft 11. Netflix 12. Oracle 13. Pinterest 14. Reddit 15. Salesforce 16. Slack 17. Spotify 18. Square 19. Target 20. Twitter 21. Uber 22. Verizon 23. Visa 24. Walmart 25. Yelp 26. Zoom 27. Airbnb 28. Dropbox 29. eBay 30. Google 31. LinkedIn 32. Amazon
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.