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Elastic Search vs Pinecone comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 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

Elastic Search
Ranking in Vector Databases
3rd
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)
Pinecone
Ranking in Vector Databases
7th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Vector Databases category, the mindshare of Elastic Search is 4.7%, down from 7.1% compared to the previous year. The mindshare of Pinecone is 7.7%, down from 9.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases
 

Featured Reviews

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.
Aakash Kushwaha - PeerSpot reviewer
Helps retrieve data, relatively cheaper, and provides useful documentation
Suppose I want to delete a vector from Pinecone or a multi-vector from a single document. Pinecone does not provide feedback on whether a document is deleted or not. In SQL and NoSQL databases, if we delete something, we get a response that it is deleted. The tool does not confirm whether a file is deleted or not. I have raised the issue with support. If we have 10,000 vectors in our index and do not use a metadata tag, it will take one to three seconds to complete a search. When I try to search using a metadata tag, the speed is still the same. The search speed must be much faster because I specify which vectors I need the data from.

Quotes from Members

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

Pros

"The solution has great scalability."
"The solution is very good with no issues or glitches."
"The most valuable feature of Elastic Enterprise Search is the Discovery option for the visualization of logs on a GPU instead of on the server."
"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."
"Elastic Search makes handling large data volumes efficient and supports complex search operations."
"The initial setup is fairly simple."
"The solution is valuable for log analytics."
"It is a stable and good platform."
"The product's setup phase was easy."
"We chose Pinecone because it covers most of the use cases."
"The semantic search capability is very good."
"The most valuable feature of Pinecone is its managed service aspect. There are many vector databases available, but Pinecone stands out in the market. It is very flexible, allowing us to input any kind of data dimensions into the platform. This makes it easy to use for both technical and non-technical users."
"The best thing about Pinecone is its private local host feature. It displays all the maintenance parameters and lets us view the data sent to the database. We can also see the status of the CD and which application it corresponds to."
"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."
 

Cons

"Better dashboards or a better configuration system would be very good."
"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."
"The real-time search functionality is not operational due to its impact on system resources."
"Scalability and ROI are the areas they have to improve."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"The GUI is the part of the program which has the most room for improvement."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"There is an index issue in which the data starts to crash as it increases."
"Pinecone can be made more budget-friendly."
"The product fails to offer a serverless type of storage capacity."
"I want to suggest that Pinecone requires a login and API key, but I would prefer not to have a login system and to use the environment directly."
"The tool does not confirm whether a file is deleted or not."
"Onboarding could be better and smoother."
"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."
 

Pricing and Cost Advice

"The tool is an open-source product."
"We are using the open-sourced version."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
"​The pricing and license model are clear: node-based model."
"We use the free version for some logs, but not extensive use."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"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 solution is relatively cheaper than other vector DBs in the market."
"I have experience with the tool's free version."
"Pinecone is not cheap; it's actually quite expensive. We find that using Pinecone can raise our budget significantly. On the other hand, using open-source options is more budget-friendly."
"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid version."
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Top Industries

By visitors reading reviews
Computer Software Company
15%
Financial Services Firm
13%
Government
9%
Manufacturing Company
9%
Computer Software Company
16%
Financial Services Firm
8%
Comms Service Provider
7%
Manufacturing Company
7%
 

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?
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...
What do you like most about Pinecone?
We chose Pinecone because it covers most of the use cases.
What needs improvement with Pinecone?
I want to suggest that Pinecone requires a login and API key, but I would prefer not to have a login system and to use the environment directly.
What is your primary use case for Pinecone?
I've used Pinecone to streamline token generation for my chatbot's functionality. Specifically, I used it for the OpenNeeam Building.
 

Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data 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.
1. Airbnb 2. DoorDash 3. Instacart 4. Lyft 5. Pinterest 6. Reddit 7. Slack 8. Snapchat 9. Spotify 10. TikTok 11. Twitter 12. Uber 13. Zoom 14. Adobe 15. Amazon 16. Apple 17. Facebook 18. Google 19. IBM 20. Microsoft 21. Netflix 22. Salesforce 23. Shopify 24. Square 25. Tesla 26. TikTok 27. Twitch 28. Uber Eats 29. WhatsApp 30. Yelp 31. Zillow 32. Zynga
Find out what your peers are saying about Elastic Search vs. Pinecone and other solutions. Updated: July 2025.
863,679 professionals have used our research since 2012.