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ClickHouse vs Redis comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 1, 2026

Review summaries and opinions

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

ROI

Sentiment score
6.8
ClickHouse boosts productivity with cost and time savings, enhancing database performance and developer efficiency significantly despite unspecified savings.
Sentiment score
7.2
Redis enhances ROI by improving performance, reducing costs, increasing productivity, and ensuring reliable, scalable, and efficient service.
I estimate we save four to five hours per person per week due to this efficiency, translating to around 20 to 25 hours saved monthly for each individual.
AIML engineer at a tech services company with 11-50 employees
We could reduce the amount of employees needed when we migrated to ClickHouse Cloud.
Founder at a tech services company with 11-50 employees
With ClickHouse, we didn't need to spend much on resources, cutting costs by around 25 to 30%.
Associate software architect at a tech services company with 11-50 employees
It improved API latency from two seconds to 450 milliseconds for P99.
Senior software developer at Makemytrip
We reduced the database read load by around 30 to 40 percent and improved API response time by 20 to 30 percent, specifically for frequently accessed endpoints.
SDE 2 at Virtusa
 

Customer Service

Sentiment score
6.6
ClickHouse offers knowledgeable support, with cloud users praising responsiveness, while community resources aid open-source user self-reliance.
Sentiment score
5.8
Redis is stable and reliable, with helpful support, strong documentation, and often minimal need for direct assistance.
If more timely support could be provided during critical issues, situations could have been resolved much more quickly, saving considerable time.
Senior Data Engineer at a transportation company with 501-1,000 employees
When we faced any challenges, the ClickHouse support team provided helpful resolutions.
AIML engineer at a tech services company with 11-50 employees
We utilize AVN ClickHouse, which is effectively managed by AVN, providing bug fixes and developing new functionalities along with architecture reviews.
Distinguished AI Leader at Walmart Global Tech at Walmart
The documentation and community support for Redis are very strong, making troubleshooting quicker.
Senior software developer at Makemytrip
Since Redis is quite stable and well-documented, we have not needed much support, but when required, the response has been helpful.
SDE 2 at Virtusa
 

Scalability Issues

Sentiment score
8.1
ClickHouse is praised for its scalability, efficiently handling large data volumes in distributed systems with solutions like AWS and Kubernetes.
Sentiment score
7.8
Redis excels in horizontal and vertical scaling, offering clustering, sharding, and compatibility with Azure and AWS for enterprise adaptability.
The vertical scalability is impressive, with high insert throughput, allowing millions of rows per second with low latency.
AIML engineer at a tech services company with 11-50 employees
ClickHouse is highly scalable.
Software Analyst at CLSA
The scalability of ClickHouse is great.
Senior Software Engineer at a wholesaler/distributor with 1,001-5,000 employees
Data migration and changes to application-side configurations are challenging due to the lack of automatic migration tools in a non-clustered legacy system.
Data Engineer at a photography company with 1,001-5,000 employees
I scale Redis horizontally using clustering and sharding, where data is distributed across multiple nodes to handle higher traffic and larger data sets.
Senior software developer at Makemytrip
With features such as clustering and replication, it can handle high traffic and a large database very effectively.
SDE 2 at Virtusa
 

Stability Issues

Sentiment score
7.7
ClickHouse offers stable, efficient performance for large data sets, with some concerns about memory use and development inconsistencies.
Sentiment score
7.8
Redis is stable, handles heavy loads, offers high availability, and uses persistence mechanisms, making it a trusted choice.
I can confidently say that it is very consistent and stable even when handling high volume loads and real-time streaming analytics across financial and operational domains.
AIML engineer at a tech services company with 11-50 employees
ClickHouse handles large volumes of data efficiently.
Software Analyst at CLSA
ClickHouse is stable, as we did not encounter stability issues in production.
Software Development Engineer at a tech vendor with 201-500 employees
Redis is fairly stable.
Data Engineer at a photography company with 1,001-5,000 employees
 

Room For Improvement

ClickHouse users seek improved documentation, integration enhancements, better cloud pricing, and solutions for operational complexity and SQL compatibility issues.
Redis users face challenges with scalability, GUI, documentation, security, and seek enhancements in monitoring, analytics, and multi-tenancy features.
Another challenge is the lack of robust support for transactional databases, which limits its use as a primary database.
Software Analyst at CLSA
ClickHouse should be able to import data from other types of sources like Parquet and Iceberg tables and all the new upcoming data formats.
Senior Software Engineer at Karvy Fintech
My experience with ClickHouse's documentation is that it needs improvement; I think it can be made more beginner-friendly, while the community support is really good.
Founder at a tech services company with 11-50 employees
Data persistence and recovery face issues with compatibility across major versions, making upgrades possible but downgrades not active.
Data Engineer at a photography company with 1,001-5,000 employees
Redis itself does not enforce consistency with the primary database, so developers need to carefully design cache invalidation strategies.
Software Engineer at ValueMomentum
One issue is cache invalidation. Keeping cache data consistent with the source of truth can be tricky, especially in distributed systems.
Senior software developer at Makemytrip
 

Setup Cost

ClickHouse offers flexible, cost-efficient pricing with open-source and cloud options, though lacks Windows support, balancing cost and performance.
Redis pricing depends on memory, cluster size, and infrastructure, with higher costs than SQL due to RAM usage.
My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option.
Founder at a tech services company with 11-50 employees
ClickHouse is open source with no hidden fees, offering cost-effective data management.
Software Analyst at CLSA
I found ClickHouse's pricing to be efficient in comparison to other services such as Redshift.
AIML engineer at a tech services company with 11-50 employees
Since we use an open-source version of Redis, we do not experience any setup costs or licensing expenses.
Data Engineer at a photography company with 1,001-5,000 employees
The costs are primarily driven by memory consumption and cluster size, since Redis operates in-memory.
Senior software developer at Makemytrip
The pricing is reasonable for the performance provided.
SDE 2 at Virtusa
 

Valuable Features

ClickHouse provides fast, scalable data storage and retrieval with seamless integration, open-source flexibility, and strong community support.
Redis offers low latency, high throughput, and scalability with rich data structures, ideal for real-time applications and caching.
ClickHouse has reduced our storage cost and improved our 99th percentile latency by 40%.
Senior Software Engineer at Karvy Fintech
For cost optimization, after deploying the cluster on-premises and using S3 Express, approximately 5x cost savings were achieved on data storage.
Senior Data Engineer at a transportation company with 501-1,000 employees
ClickHouse positively impacted our organization by absorbing the whole logging system without hassle, storing logs for six months efficiently.
Associate software architect at a tech services company with 11-50 employees
It functions similarly to a foundational building block in a larger system, enabling native integration and high functionality in core data processes.
Data Engineer at a photography company with 1,001-5,000 employees
First is its in-memory preference, as Redis is extremely fast, making it ideal for caching and session management where low latency is critical.
Software Engineer at ValueMomentum
Real API latency improved from around two seconds to approximately 450 milliseconds for P99.
Senior software developer at Makemytrip
 

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 (3rd)
Redis
Ranking in Vector Databases
4th
Average Rating
8.8
Reviews Sentiment
5.9
Number of Reviews
26
Ranking in other categories
NoSQL Databases (4th), Managed NoSQL Databases (6th), In-Memory Data Store Services (1st), AI Software Development (13th)
 

Mindshare comparison

As of May 2026, in the Vector Databases category, the mindshare of ClickHouse is 5.6%, up from 3.6% compared to the previous year. The mindshare of Redis is 5.7%, up from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Redis5.7%
ClickHouse5.6%
Other88.7%
Vector Databases
 

Featured Reviews

reviewer2785038 - PeerSpot reviewer
Senior Data Engineer at a transportation company with 501-1,000 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.
Varuns Ug - PeerSpot reviewer
Senior software developer at Makemytrip
Caching has accelerated complex workflows and delivers low latency for high-traffic microservices
A few features of Redis that I use on a day-to-day basis and feel are among the best are extremely low latency and high throughput. Since Redis is in-memory, it makes it ideal for cases such as caching and rate limiting where response time is critical. TTL expiry support is very useful in Redis as it allows me to automatically evict stale data without manual cleanup, which is something I use heavily in my caching strategy. Another point I can mention is that the rich data structures such as strings, hashes, and even sorted sets are very powerful. I have used strings for caching responses and counters, whereas I have used hashes for storing structured objects. One more feature I can tell you about is atomic operations. Redis guarantees atomicity for operations such as incrementing a counter, which is very useful for rate limiting and avoiding race conditions in distributed systems. Finally, I want to emphasize that Redis is easy to scale and integrate, whether through clustering or using a distributed cache across microservices. Redis has impacted my organization positively by providing default support that is very useful. For metrics, in one of my core systems, introducing Redis as a distributed cache helped me achieve around an 80% cache hit rate, which reduced repeated downstream services. Real API latency also improved from around two seconds to approximately 450 milliseconds for P99. It also helped reduce the load on dependent services and databases, which improved overall system reliability.
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
14%
Outsourcing Company
8%
Comms Service Provider
8%
Financial Services Firm
24%
Computer Software Company
10%
Comms Service Provider
7%
University
6%
 

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 Business11
Midsize Enterprise6
Large Enterprise10
 

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 Redis?
Redis is better tested and is used by large companies. I haven't found a direct alternative to what Redis offers. Plus, there are a lot of support and learning resources available, which help you u...
What needs improvement with Redis?
Overall, Redis is a powerful and reliable tool, but there are a few areas for improvement. One limitation is that Redis is memory-based, so scaling can become expensive compared to disk-based syste...
What is your primary use case for Redis?
My main use case for Redis is caching frequently accessed data to improve performance and reduce database load. For example, I cache API responses and user-related data so that repeated requests ca...
 

Comparisons

 

Also Known As

No data available
Redis Enterprise
 

Overview

 

Sample Customers

Information Not Available
1. Twitter 2. GitHub 3. StackOverflow 4. Pinterest 5. Snapchat 6. Craigslist 7. Digg 8. Weibo 9. Airbnb 10. Uber 11. Slack 12. Trello 13. Shopify 14. Coursera 15. Medium 16. Twitch 17. Foursquare 18. Meetup 19. Kickstarter 20. Docker 21. Heroku 22. Bitbucket 23. Groupon 24. Flipboard 25. SoundCloud 26. BuzzFeed 27. Disqus 28. The New York Times 29. Walmart 30. Nike 31. Sony 32. Philips
Find out what your peers are saying about ClickHouse vs. Redis and other solutions. Updated: April 2026.
893,164 professionals have used our research since 2012.