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ClickHouse 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

ClickHouse
Ranking in Vector Databases
11th
Average Rating
8.8
Reviews Sentiment
7.8
Number of Reviews
11
Ranking in other categories
Open Source Databases (6th)
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 ClickHouse is 3.8%, up from 1.4% 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

Aswini Atibudhi - PeerSpot reviewer
Provides real-time data insights with high flexibility and responsive support
The basic challenge for ClickHouse is the documentation, which isn't ideal, but it's mature and stable with more columnar storage, compression, and parallel processing, making it the best for OLAP. In terms of improvements, it's not designed for very frequent small writes, making it less scalable in write-intensive workloads, and it's not flourishing in transactional use cases or when ingesting streaming data, such as batching or buffering, which is something ClickHouse will improve.
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 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."
"ClickHouse is very easy to use; one of the good features is that it has joins, which were not present in Druid, and Druid was quite expensive, especially with our applications at Sam's Club utilizing ClickHouse very quickly."
"ClickHouse is a user-friendly solution that tries to be compatible with SQL standards."
"The tool is column-based and infinitely scalable."
"We faced a challenge with deploying ClickHouse onto Kubernetes. Recently, we've been using ClickHouse Cloud, and the main issue is the high cost of the cloud service. The pricing isn't very competitive, especially for startups. I would instead buy a server and self-host if I have enough disk space. Besides that, ClickHouse has done very well, with clear goals and effective execution."
"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."
"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."
"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 most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."
"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 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 semantic search capability is very good."
 

Cons

"The main issue is the lack of documentation. Many features are available but are not fully documented, which can make finding information challenging."
"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."
"If you join our team, it should be easy for you to use ClickHouse, especially if you are a developer. However, you need to read the documentation and understand the problems you are trying to solve."
"There are some areas where ClickHouse could improve. Specifically, we encountered incompatibilities with its SQL syntax when migrating queries from MySQL or SQL to ClickHouse. This difference in details made it challenging to figure out the exact issues. Additionally, we faced difficulties due to the lack of a proper Django driver for ClickHouse, unlike MySQL, which Django supports out of the box."
"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."
"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."
"In terms of improvements, it's not designed for very frequent small writes, making it less scalable in write-intensive workloads, and it's not flourishing in transactional use cases or when ingesting streaming data, such as batching or buffering, which is something ClickHouse will improve."
"We had a lot of troubles while deploying a whole cluster."
"Onboarding could be better and smoother."
"Pinecone can be made more budget-friendly."
"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 product fails to offer a serverless type of storage capacity."
"The tool does not confirm whether a file is deleted or not."
"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."
 

Pricing and Cost Advice

"ClickHouse has an open-source version, which is free to use and has almost all the features."
"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."
"We used the free, community version of ClickHouse."
"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."
"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."
"The tool is open-source."
"The tool is free."
"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."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
24%
Financial Services Firm
15%
Educational Organization
11%
Manufacturing Company
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 is your experience regarding pricing and costs for ClickHouse?
ClickHouse is open source without direct fees, unlike other databases that have hidden fees or restrict hosting to their platforms. The open-source nature of ClickHouse allows for complete flexibil...
What needs improvement with ClickHouse?
The basic challenge for ClickHouse is the documentation, which isn't ideal, but it's mature and stable with more columnar storage, compression, and parallel processing, making it the best for OLAP....
What is your primary use case for ClickHouse?
I have experience in ClickHouse ( /products/clickhouse-reviews ), and we also use Apache Druid ( /products/druid-reviews ), which has corporate support from Druid ( /products/druid-reviews ), along...
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

 

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: June 2025.
860,592 professionals have used our research since 2012.