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ClickHouse vs Pulse Elasticsearch and OpenSearch comparison

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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
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
21
Ranking in other categories
Open Source Databases (3rd), Vector Databases (8th)
Pulse Elasticsearch and Ope...
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
Indexing and Search (16th)
 

Mindshare comparison

ClickHouse and Pulse Elasticsearch and OpenSearch aren’t in the same category and serve different purposes. ClickHouse is designed for Open Source Databases and holds a mindshare of 6.3%, up 6.0% compared to last year.
Pulse Elasticsearch and OpenSearch, on the other hand, focuses on Indexing and Search, holds 1.5% mindshare.
Open Source Databases Mindshare Distribution
ProductMindshare (%)
ClickHouse6.3%
MySQL12.7%
PostgreSQL11.5%
Other69.5%
Open Source Databases
Indexing and Search Mindshare Distribution
ProductMindshare (%)
Pulse Elasticsearch and OpenSearch1.5%
Elastic Search9.6%
OpenText Knowledge Discovery (IDOL)6.6%
Other82.3%
Indexing and Search
 

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.
Rafayel Agamyan - PeerSpot reviewer
DevOps Engineer at a tech vendor with 1,001-5,000 employees
Search performance has transformed customer document access and continues to improve satisfaction
Customer satisfaction has significantly improved since switching to Pulse Elasticsearch and OpenSearch from old legacy services, as many insights from customers indicate that latency has changed dramatically and the speed is significantly better now. For others looking into using Pulse Elasticsearch and OpenSearch, it is definitely recommended to give it a try, especially if old legacy systems that are slow are currently being used. Lately, OpenSearch has come up with a new version that greatly enhances speed, so trying it is encouraged and it will be loved. A review rating of 9 reflects the overall satisfaction with Pulse Elasticsearch and OpenSearch.

Quotes from Members

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

Pros

"ClickHouse provides responses within a few seconds, typically two to three seconds, which is impressive."
"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."
"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."
"ClickHouse has positively impacted my organization, as there was an entire exercise done on which database we were supposed to use for solving our problems, and we found ClickHouse was the one performing the best, which is when we adopted it."
"ClickHouse has positively impacted my organization by replacing PostgreSQL, which required complex foreign tables for queries, and with ClickHouse we now have Cube.js for easier data visualization."
"<p>We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case.</p>"
"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."
"It is quite easy, and I think it was really great the way they offered the services."
"Customer satisfaction has significantly improved since switching to Pulse Elasticsearch and OpenSearch from old legacy services, as many insights from customers indicate that latency has changed dramatically and the speed is significantly better now."
 

Cons

"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."
"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."
"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."
"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."
"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."
"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."
"ClickHouse can be improved, and the main challenge I see is its operational complexity."
"I think the way they support the ingesting service for Pulse Elasticsearch and OpenSearch is not really great."
 

Pricing and Cost Advice

"ClickHouse has an open-source version, which is free to use and has almost all the features."
"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."
"The tool is open-source."
"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 free."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Comms Service Provider
11%
Outsourcing Company
11%
Computer Software Company
10%
Construction Company
28%
Financial Services Firm
16%
Healthcare Company
11%
Comms Service Provider
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise5
Large Enterprise8
No data available
 

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 is your primary use case for Pulse Elasticsearch and OpenSearch?
My primary use case is powering up the search in the product.
What advice do you have for others considering Pulse Elasticsearch and OpenSearch?
I have not used the SQL query support feature. I did assess the RESTful API support. I have not utilized Pulse Elasticsearch and OpenSearch machine learning features, as there was no use case for m...
What needs improvement with Pulse Elasticsearch and OpenSearch?
I think the way they support the ingesting service for Pulse Elasticsearch and OpenSearch is not really great. If I got to attach a few more records, they don't support it. It's all rewrite every t...
 

Overview

Find out what your peers are saying about Oracle, PostgreSQL, ClickHouse and others in Open Source Databases. Updated: October 2026.
920,769 professionals have used our research since 2012.