

InfluxDB and ClickHouse compete in the time-series and analytical database categories. ClickHouse seems to have the upper hand in performance and scalability, appealing to enterprises needing advanced analytical capabilities.
Features: InfluxDB offers native time-series data processing, a rich query language, and efficient handling of large volumes of data with minimal setup. ClickHouse provides high-speed data ingestion, complex querying, and advanced analytics suited for real-time applications.
Room for Improvement: InfluxDB could enhance its analytical capabilities and scalability options. Its integration with non-time-series data could be expanded. ClickHouse may benefit from simplifying its deployment process and enhancing compatibility with other systems. Its technical support options could also be more user-friendly.
Ease of Deployment and Customer Service: InfluxDB is known for simple deployment and supportive documentation. It is user-friendly in metrics collection, offering community resources. ClickHouse requires more intricate setup but provides strong technical support that benefits organizations with robust IT infrastructures.
Pricing and ROI: InfluxDB offers cost-effective pricing models, particularly for startups and smaller businesses, enhancing ROI with efficient data management. ClickHouse, though potentially costlier, offers substantial value for enterprises needing high performance and advanced analytics, justifying the investment through superior speed and scalability.
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.
We could reduce the amount of employees needed when we migrated to ClickHouse Cloud.
With ClickHouse, we didn't need to spend much on resources, cutting costs by around 25 to 30%.
InfluxDB reduced my time to show data without any interruption, also reducing the number of people needed to manage the project; it is very good to have InfluxDB in my project.
Time saved is there, as I mentioned, because we have an analytics system from where we get alerting and monitoring.
If more timely support could be provided during critical issues, situations could have been resolved much more quickly, saving considerable time.
When we faced any challenges, the ClickHouse support team provided helpful resolutions.
We utilize AVN ClickHouse, which is effectively managed by AVN, providing bug fixes and developing new functionalities along with architecture reviews.
The vertical scalability is impressive, with high insert throughput, allowing millions of rows per second with low latency.
ClickHouse is highly scalable.
The scalability of ClickHouse is great.
The main challenge with InfluxDB, which is common with all databases, was handling very high throughput systems and high throughput message flow.
We’ve scaled on volume with seven years of continuous data without performance degradation.
InfluxDB's scalability is fine for me; I gather a lot of metrics and have not had any issues.
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.
ClickHouse handles large volumes of data efficiently.
ClickHouse is stable, as we did not encounter stability issues in production.
It serves as the backbone of our application, and its stability is crucial.
It is very stable, with no reliability or downtime in InfluxDB.
After integrating Kafka, it never broke again, as Kafka handled messages and metrics appropriately, decreasing the message throughput.
Another challenge is the lack of robust support for transactional databases, which limits its use as a primary database.
ClickHouse should be able to import data from other types of sources like Parquet and Iceberg tables and all the new upcoming data formats.
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.
InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying.
Having a SQL abstraction in InfluxDB could be beneficial, making it more accessible for teams that prefer querying with SQL-style syntax.
It could include automated backup and a monitoring solution for InfluxDB or a script developed by a REST API.
My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option.
ClickHouse is open source with no hidden fees, offering cost-effective data management.
I found ClickHouse's pricing to be efficient in comparison to other services such as Redshift.
We use the open-source version of InfluxDB, so it is free.
My experience with pricing, setup cost, and licensing for InfluxDB was great, as I did not use any license.
We are using an open-source solution, so there is no cost on that.
ClickHouse has reduced our storage cost and improved our 99th percentile latency by 40%.
For cost optimization, after deploying the cluster on-premises and using S3 Express, approximately 5x cost savings were achieved on data storage.
ClickHouse positively impacted our organization by absorbing the whole logging system without hassle, storing logs for six months efficiently.
The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading.
InfluxDB’s core functionality is crucial as it allows us to store our data and execute queries with excellent response times.
It helps me maintain my solution easily because it is very reliable, so we didn't face any performance issues or crashes regarding our queries; we can get the results very fast.
| Product | Market Share (%) |
|---|---|
| ClickHouse | 6.5% |
| InfluxDB | 5.0% |
| Other | 88.5% |

| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 4 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 3 |
| Large Enterprise | 8 |
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?
What benefits should users consider?
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.
InfluxDB is open-source software that helps developers and enterprises alike to collect, store, process, and visualize time series data and to build next-generation applications. InfluxDB provides monitoring and insight on IoT, application, system, container, and infrastructure quickly and easily without complexities or compromises in scale, speed, or productivity.
InfluxDB has become a popular insight system for unified metrics and events enabling the most demanding SLAs. InfluxDB is used in just about every type of industry across a wide range of use cases, including network monitoring, IoT monitoring, industrial IoT, and infrastructure and application monitoring.
InfluxDB offers its users:
InfluxDB Benefits
There are several benefits to using InfluxDB . Some of the biggest advantages the solution offers include:
Reviews from Real Users
InfluxDB stands out among its competitors for a number of reasons. Two major ones are its flexible integration options and its data aggregation feature.
Shalauddin Ahamad S., a software engineer at a tech services company, notes, “The most valuable features are aggregating the data and the integration with Grafana for monitoring.”
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