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ChatGPT Team - Enterprise vs OpenSearch comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 14, 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 Team - Enterprise
Average Rating
8.6
Reviews Sentiment
5.6
Number of Reviews
16
Ranking in other categories
AI Writing Tools (2nd), AI Code Assistants (5th), Large Language Models (LLMs) (2nd), AI Proofreading Tools (2nd)
OpenSearch
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
Open Source Databases (14th), Vector Databases (8th)
 

Mindshare comparison

ChatGPT Team - Enterprise and OpenSearch aren’t in the same category and serve different purposes. ChatGPT Team - Enterprise is designed for Large Language Models (LLMs) and holds a mindshare of 9.2%, up 6.5% compared to last year.
OpenSearch, on the other hand, focuses on Open Source Databases, holds 4.6% mindshare, down 5.1% since last year.
Large Language Models (LLMs) Market Share Distribution
ProductMarket Share (%)
ChatGPT Team - Enterprise9.2%
Blackbox.ai16.7%
Google Gemini AI15.5%
Other58.6%
Large Language Models (LLMs)
Open Source Databases Market Share Distribution
ProductMarket Share (%)
OpenSearch4.6%
PostgreSQL14.3%
Firebird SQL12.5%
Other68.6%
Open Source Databases
 

Featured Reviews

Vyas Shubham - PeerSpot reviewer
Product Analyst at MA
Centralized knowledge has transformed collaboration and now streamlines documentation work
ChatGPT Team - Enterprise is already a very strong AI tool, but some improvements could enhance it further. Currently, context depends on what is provided, the prompts, and what is in memory. An improvement could be the automatic suggestion of relevant files or context based on queries. Cross-document semantic linking could be beneficial. Better handling of evolving knowledge would be useful, such as showing what changes have been made since last month. Additionally, teams want finer permissions such as read-only memory groups and scoped templates by role, departments, and temporary access tokens for contractors. I feel that more granular access controls are needed. Beyond APIs, teams now want no-code automations, including the ability to trigger summary generation after meetings, classification of support tickets, and scheduling of reports. Another improvement that comes to mind is the implementation of an in-app learning and training program. Built-in tutorials could help the team discover more advanced features and learn how to provide better prompts. The platform should provide best practices that show users what they need to do to get the best results. An in-app learning or training program would be valuable.
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Top Industries

By visitors reading reviews
Computer Software Company
11%
Comms Service Provider
11%
Manufacturing Company
8%
University
7%
Financial Services Firm
18%
Computer Software Company
12%
Manufacturing Company
10%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise3
Large Enterprise7
No data available
 

Questions from the Community

What needs improvement with ChatGPT?
In terms of improvements needed for ChatGPT Team - Enterprise, accuracy still requires enhancement in complex or high-domain specific scenarios, particularly architecture and security topics. Respo...
What is your primary use case for ChatGPT?
My primary use case for ChatGPT Team - Enterprise is supporting day-to-day work across engineering, products, QA, and customer support teams, mainly using it for code assistance, technical document...
What advice do you have for others considering ChatGPT?
ChatGPT Team - Enterprise is deployed in my organization through a secure public cloud-based SaaS model, accessed via authenticated enterprise accounts, integrating into my existing workflows and t...
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Also Known As

Rockset
No data available
 

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
1. Amazon 2. Netflix 3. Yelp 4. Adobe 5. IBM 6. Microsoft 7. Cisco 8. Oracle 9. Salesforce 10. eBay 11. Spotify 12. Airbnb 13. Twitter 14. LinkedIn 15. Pinterest 16. Slack 17. Dropbox 18. Expedia 19. Uber 20. Lyft 21. Square 22. Zillow 23. Reddit 24. Hulu 25. Twitch 26. Booking.com 27. Etsy 28. Groupon 29. StubHub 30. TripAdvisor 31. Wayfair 32. Zappos
Find out what your peers are saying about Google, OpenAI, Blackbox and others in Large Language Models (LLMs). Updated: January 2026.
882,606 professionals have used our research since 2012.