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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

"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."
"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."
"It is easy to scale with the cluster node model.​"
"It helps us to analyse the logs based on the location, user, and other log parameters."
"The solution is quite scalable and this is one of its advantages."
"Data indexing of historical data is the most beneficial feature of the product."
"The special text processing features in this solution are very important for me."
"Elastic Search makes handling large data volumes efficient and supports complex search operations."
"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."
"We chose Pinecone because it covers most of the use cases."
"The semantic search capability is very good."
"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."
"The product's setup phase was easy."
"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."
 

Cons

"Elasticsearch could be improved in terms of scalability."
"I would like to be able to do correlations between multiple indexes."
"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."
"There should be more stability."
"There are challenges with performance management and scalability."
"New Relic could be more flexible, similar to Elasticsearch."
"Elastic Search should provide better guides for developers."
"The one area that can use improvement is the automapping of fields."
"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."
"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."
"The tool does not confirm whether a file is deleted or not."
"The product fails to offer a serverless type of storage capacity."
"Onboarding could be better and smoother."
"Pinecone can be made more budget-friendly."
 

Pricing and Cost Advice

"The tool is not expensive. Its licensing costs are yearly."
"I rate Elastic Search's pricing an eight out of ten."
"We use the free version for some logs, but not extensive use."
"we are using a licensed version of the product."
"The solution is not expensive because users have the option of choosing the managed or the subscription model."
"This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
"It can be expensive."
"The solution is affordable."
"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
14%
Manufacturing Company
9%
Government
9%
Computer Software Company
17%
Financial Services Firm
9%
Manufacturing Company
8%
Comms Service Provider
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: June 2025.
861,524 professionals have used our research since 2012.