ClickHouse vs Pinecone comparison

ClickHouse and Pinecone are both solutions in the Vector Databases category. ClickHouse is ranked #7 with an average rating of 8.6, while Pinecone is ranked #5 with an average rating of 8.3. ClickHouse holds a 4.9% mindshare in VD, compared to Pinecone’s 7.1% mindshare. Additionally, 100% of ClickHouse users are willing to recommend the solution, compared to 100% of Pinecone users who would recommend it.

ClickHouse

Read 21 ClickHouse reviews

4,128 Views
1,651 Comparison Views

100% willing to recommend

Pinecone

Read 9 Pinecone reviews

3,390 Views
3,119 Comparison Views

100% willing to recommend

ClickHouse

Pinecone

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 23, 2025

Pinecone and ClickHouse compete in the data management category, each with distinct advantages. Pinecone appears to excel in areas like pricing and deployment simplicity, whereas ClickHouse provides outstanding analytical features and long-term value.

Features: Pinecone offers scalable and easy-to-integrate vector databases ideal for real-time recommendations and semantic searches. It supports seamless scalability, efficient data storage, and vector search capabilities. ClickHouse is known for its high-performance analytical capabilities, efficient data querying, and the ability to handle large-scale data workloads effectively.

Room for Improvement: Pinecone could enhance its analytical feature set, expand support for more complex queries, and improve its integration capabilities with other tools. ClickHouse may need to simplify its configuration process, reduce the complexity associated with its maintenance, and improve its support for real-time data processing scenarios.

Ease of Deployment and Customer Service: Pinecone's cloud-native architecture simplifies deployment and its proactive support aids swift integration. ClickHouse, though offering great flexibility with its open-source framework, requires extensive configuration and maintenance, demanding technical expertise and offering substantial configuration freedom.

Pricing and ROI: Pinecone is cost-effective, focusing on delivering high ROI with low initial costs and efficient performance, making it attractive for budget-conscious clients. ClickHouse may incur higher setup costs due to infrastructure requirements but offers significant long-term benefits with its robust data processing capabilities, promising excellent ROI through its exceptional data handling efficiency.

To learn more, read our detailed ClickHouse vs. Pinecone Report (Updated: December 2025).

Buyer's Guide

ClickHouse vs. Pinecone

December 2025

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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

Ranking in other categories

Open Source Databases (4th)

Pinecone

Ranking in Vector Databases

5th

Average Rating

8.4

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

AI Data Analysis (15th), AI Content Creation (4th)

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of ClickHouse is 4.9%, up from 2.5% compared to the previous year. The mindshare of Pinecone is 7.1%, down from 8.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Pinecone	7.1%
ClickHouse	4.9%
Other	88.0%

Vector Databases

Featured Reviews

Yush Mittal

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.

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Pradeep Gudipati

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.

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Quotes from Members

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

Pros

"There is no better option than ClickHouse in all OLAP-based databases, so I think it is best to use ClickHouse in that regard."

"ClickHouse is much faster than traditional databases like MySQL and MongoDB. Its column-row searching strategy makes it very efficient. With ClickHouse, we can manage multiple databases, automatically insert data from other databases and delete data as needed. It supports real-time query performance, allowing simultaneous data insertion and retrieval. ClickHouse has improved significantly over the past two years, adding more functions and queries, as well as top functionality."

"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."

"ClickHouse provides great query speeds because it is an OLAP database, so naturally, it provides higher speeds."

"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."

"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."

"It's easier to work with big data and calculations using the product."

"ClickHouse Cloud saves a lot of time for our DevOps engineers since there isn't much deployment involved and everything is served directly, leading to increased efficiency and productivity."

More ClickHouse pros

"The product's setup phase was easy."

"Pinecone has positively impacted my organization by helping people in needle-in-a-haystack situations, as previously they had to grind through PDF documents, PowerPoint documents, and websites, but now with Pinecone, they can ask questions and receive references to documents along with the page numbers where that information exists, so they can use it as a reference or backtrack, especially for things such as FDA approvals where they can quote the exact page number from PDF documents, eliminating hallucination and providing real-time data that relies on an external vector database with enough guardrails to ensure it won't provide information not in the vector database, confining it to the information present in the indexes."

"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."

"Pinecone's integration with AWS was seamless."

"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."

"We chose Pinecone because it covers most of the use cases."

"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."

More Pinecone pros

Cons

"I chose nine out of ten because, as I mentioned, the improvement side and the ten thousand partition limit created issues that we were hitting quite frequently, but with some schema manipulations we did manage to find a workaround, although that could have been avoided had things been better documented on how we could have solved this problem in a different approach, which took some bandwidth."

"The open-source version of ClickHouse is not very scalable."

"My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option."

"I would like ClickHouse to work more on integration with third-party tools."

"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."

"We had a lot of troubles while deploying a whole cluster."

"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."

"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."

More ClickHouse cons

"If Pinecone gave us RAG as a service, we'd be more than happy to use that."

"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."

"Onboarding could be better and smoother."

"The tool does not confirm whether a file is deleted or not."

"The product fails to offer a serverless type of storage capacity."

"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."

"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."

More Pinecone cons

Pricing and Cost Advice

"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 Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."

"ClickHouse has an open-source version, which is free to use and has almost all the features."

"The tool is free."

"We used the free, community version of ClickHouse."

"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 open-source."

"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid 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 have experience with the tool's free 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

17%

Computer Software Company

16%

Manufacturing Company

Educational Organization

Computer Software Company

14%

University

Manufacturing Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	13
Midsize Enterprise	4
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	2
Large Enterprise	3

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...

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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 ...

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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...

See all answers

What do you like most about Pinecone?

We chose Pinecone because it covers most of the use cases.

See all answers

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...

See all answers

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...

See all answers

Comparisons

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Compared 13% of the time

OpenSearch vs ClickHouse

Compared 9% of the time

VictoriaMetrics vs ClickHouse

Compared 7% of the time

Cassandra vs ClickHouse

Compared 7% of the time

Milvus vs ClickHouse

Compared 6% of the time

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Supabase Vector vs Pinecone

Compared 32% of the time

Microsoft Azure Cosmos DB vs Pinecone

Compared 13% of the time

OpenSearch vs Pinecone

Compared 10% of the time

LanceDB vs Pinecone

Compared 6% of the time

Marqo vs Pinecone

Compared 2% of the time

More Pinecone Competitors

Product Reports

Buyer's Guide

ClickHouse

January 2026

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Buyer's Guide

Pinecone

January 2026

Download Pinecone product report

Overview

ClickHouse is renowned for its speed, scalability, and real-time query performance. Its compatibility with SQL standards enhances flexibility while enabling integration with popular tools.

ClickHouse leverages a column-based architecture for efficient data compression and real-time analytics. It seamlessly integrates with tools like Kafka and Tableau and is effective in handling large datasets due to its cost-efficient aggregation capabilities. With robust data deduplication and strong community backing, users can access comprehensive documentation and up-to-date functionality. However, improvements in third-party integration, cloud deployment, and handling of SQL syntax differences are noted, impacting ease-of-use and migration from other databases.

What features make ClickHouse outstanding?

Speed and Scalability: Enables rapid deployment and scalability, particularly on Kubernetes.
SQL Compatibility: Aligns with SQL standards for flexible database management.
Column-based Structure: Offers efficient data compression and quick query performance.
Integration Support: Works with Kafka, Tableau, and other popular platforms.
Data Deduplication: Manages complex data duplication efficiently.

What benefits should users consider?

Cost-Efficiency: Reduces expenses while managing large datasets effectively.
Real-Time Analytics: Provides fast data processing for real-time insights.
Flexibility: Offers multiple integration points and compatibility options.
Robust Documentation: Backed by an active development community, ensuring comprehensive support.

ClickHouse is deployed in sectors like telecommunications for passive monitoring and is beneficial for data analytics, logging Clickstream data, and as an ETL engine. Organizations harness it for machine learning applications when combined with GPT. With the ability to be installed independently, it's an attractive option for avoiding cloud service costs.

ClickHouse

Pinecone is a powerful tool for efficiently storing and retrieving vector embeddings. It is highly praised for its scalability, speed, and ease of integration with existing workflows.

Users find it particularly useful for similarity search, recommendation systems, and natural language processing.

Its efficient search capabilities, seamless integration with existing systems, and ability to handle large-scale datasets make it a valuable tool for data analysis and retrieval.

Pinecone

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

Buyer's Guide

ClickHouse vs. Pinecone

December 2025

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