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ClickHouse vs Pinecone comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 23, 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

ClickHouse
Ranking in Vector Databases
7th
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
21
Ranking in other categories
Open Source Databases (4th)
Pinecone
Ranking in Vector Databases
6th
Average Rating
8.4
Reviews Sentiment
6.5
Number of Reviews
9
Ranking in other categories
AI Data Analysis (14th), AI Content Creation (3rd)
 

Mindshare comparison

As of January 2026, in the Vector Databases category, the mindshare of ClickHouse is 4.7%, up from 2.4% compared to the previous year. The mindshare of Pinecone is 7.3%, down from 8.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
Pinecone7.3%
ClickHouse4.7%
Other88.0%
Vector Databases
 

Featured Reviews

Yush Mittal - PeerSpot reviewer
Level 2 Software Engineer at a computer software company with 201-500 employees
Data observability has enabled real‑time analytics and cost savings but needs smoother inserts and cleanup
ClickHouse could be improved concerning data insertion, especially given the high amount of data handled. Constant efforts are made to optimize the features on its own, but with merges and inserts, only a single insert query can be performed allowing for the input of only 100,000 rows per second. It would be beneficial to insert more data and have configurations that are less user-operated. Ideally, ClickHouse would optimize itself to handle these processes automatically, reducing the need to contact the ClickHouse support team for infrastructure optimization. Additionally, delays are experienced when trying to delete databases with corrupt data, taking too much time and causing major outages, which necessitate contacting multiple teams across continents for resolution. The community surrounding ClickHouse also seems limited, providing a reliance on documentation, and there is a scarcity of developers working with ClickHouse, which hinders growth. If ClickHouse were more user-friendly and technically feasible, it would likely see greater expansion in usage.
Pradeep Gudipati - PeerSpot reviewer
Chief Technology Advisor at Kovaad technologies Pvt Ltd
Faced challenges with metadata filtering but have achieved reliable long-term memory for chat applications
We were looking at multiple options for a vector database, and we found Pinecone to be the easiest to integrate into our solution. Plus, it has a very generous free tier, which helps us as a startup. The best features Pinecone offers are quick setup and good indexing for us. The retrieval mechanisms are fast, and the integration with Python as with JavaScript and TypeScript libraries that Pinecone provides are very robust. Authentication is also very good. The namespaces feature allows us to break down or store data for each user separately, reducing interference and maintaining privacy as an important feature. Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database. We are seeing that the trainees getting trained on the platform are more satisfied with the results or messages generated by AI.

Quotes from Members

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

Pros

"If you have a real-time basis, you should take a look at ClickHouse because it works on a vector database, and the querying is super fast compared to traditional databases."
"The tool is column-based and infinitely scalable."
"The best thing about the tool is that I can set it up on my computer and run queries without depending on the cloud. This is why I use it every day."
"Regarding performance, we tried multiple solutions when Kibana was failing, including PostgreSQL, MySQL, and even MongoDB for log ingestion of huge volumes, but ClickHouse outperformed all databases we tested, leading us to choose it for further use cases."
"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."
"ClickHouse is a user-friendly solution that tries to be compatible with SQL standards."
"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."
"ClickHouse is open source with no vendor lock-in, providing excellent freedom to choose any vendor without restrictions."
"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."
"The semantic search capability is very good."
"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."
"We chose Pinecone because it covers most of the use cases."
"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."
"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."
 

Cons

"The aggregation capability is a valuable feature. It's highly efficient, allowing us to review entire transaction histories and user activities in the market. We've tried MongoDB, Postgres, MariaDB, and BigQuery, but ClickHouse is the most cost-efficient solution for collecting data at high speeds with minimal cost. We even used ClickHouse Cloud for a month, and it proved to be a great setup, especially for startups looking to handle big data. For example, if there is a need for 2-4 terabytes of data and around 40 billion rows with reasonable computing speed and latency, ClickHouse is ideal. Regarding the real-time query performance of ClickHouse, when using an API server to query it, I achieved query results in less than twenty milliseconds in some of my experiments with one billion rows. However, it depends on the scenario since ClickHouse has limitations in handling mutations. Additionally, one of ClickHouse's strengths is its compression capability. Our experimental server has only four terabytes, and ClickHouse effectively compresses data, allowing us to store large amounts of data at high speed. This compression efficiency is a significant advantage of using ClickHouse."
"The main issue is the lack of documentation. Many features are available but are not fully documented, which can make finding information challenging."
"In terms of needed improvements, some enhancements in documentation are necessary."
"Initially, I faced challenges integrating ClickHouse, particularly with inserting data from ActiveMQ, which caused duplicates. However, after adjusting the ClickHouse settings, the issue was resolved and there were no more duplicates."
"Too many issues exist for beginners to set up ClickHouse. Many parameters must be configured, such as maximum scatter part settings that determine when writing to a table stops."
"We would like to have fuzzy search capabilities in ClickHouse like we had with Kibana because there are scenarios where we cannot search keywords fuzzily in ClickHouse, whereas Elasticsearch allows that, and in such cases, Elasticsearch outperforms ClickHouse."
"Additionally, delays are experienced when trying to delete databases with corrupt data, taking too much time and causing major outages, which necessitate contacting multiple teams across continents for resolution."
"There aren't too many improvements I'd suggest for ClickHouse as it covers all my needs. There are just a few technical issues. For example, sometimes, when you want to get unique values and use certain tables, they don't work as expected. But it's not a major problem."
"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."
"Pinecone can be made more budget-friendly."
"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."
"If Pinecone gave us RAG as a service, we'd be more than happy to use that."
"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."
"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."
"Pinecone is good as it is, but had it been on AWS infrastructure, we wouldn't experience some network lags because it's outside AWS."
 

Pricing and Cost Advice

"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."
"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."
"The tool is free."
"The tool is open-source."
"For pricing, if you use the self-hosted version, it would be free. Cloud services pricing would be an eight out of ten. I try to minimize costs but still have to monitor usage."
"ClickHouse has an open-source version, which is free to use and has almost all the features."
"We used the free, community version of ClickHouse."
"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 have experience with the tool's free version."
"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid version."
"The solution is relatively cheaper than other vector DBs in the market."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
16%
Manufacturing Company
8%
Comms Service Provider
8%
Computer Software Company
14%
Manufacturing Company
8%
Comms Service Provider
7%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise4
Large Enterprise8
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise3
 

Questions from the Community

What is your experience regarding pricing and costs for ClickHouse?
My experience with pricing, setup cost, and licensing was such that the setup costs were just my own bandwidth, while licensing and pricing were done by other members of the team so it was abstract...
What needs improvement with ClickHouse?
ClickHouse can be improved on the documentation side, and there is one small constraint that is mentioned in ClickHouse documentation, which is a partition limit of ten thousand that we hit, so if ...
What is your primary use case for ClickHouse?
My main use case for ClickHouse is data ingestion and for its OLAP properties, as we had use cases where database locks were slowing us down and because ClickHouse does not have that, we chose to u...
What do you like most about Pinecone?
We chose Pinecone because it covers most of the use cases.
What needs improvement with Pinecone?
I give Pinecone a nine out of ten because I hope it provides an end-to-end agentic solution, but currently, it doesn't have those agentic capabilities, meaning I have to create a Streamlit applicat...
What is your primary use case for Pinecone?
My main use case for Pinecone is creating vector indexes for GenAI applications. A specific example of how I use Pinecone in one of my projects is utilizing a RAG pipeline where I take text from PD...
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
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 ClickHouse vs. Pinecone and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.