

PostgreSQL and ClickHouse both operate in the database industry, specifically catering to different types of workloads. While PostgreSQL is versatile for OLTP and analytical tasks, ClickHouse is better suited for OLAP workloads due to its performance capabilities.
Features: PostgreSQL is rich in features, supported by robust indexing, an excellent query optimization engine, and spatial support with GIS capabilities. Its open-source nature and comprehensive documentation make it user-friendly. ClickHouse is designed for fast querying and real-time data analysis, offering powerful OLAP functions, efficient data aggregation, and columnar storage for optimal performance.
Room for Improvement: PostgreSQL could enhance its replication support, develop better GUI tools, and improve memory management. ClickHouse might benefit from enhancing its SQL syntax support, documentation quality, and integrating with third-party tools. Simplifying operational complexity and incorporating real-time deduplication would also be advantageous for ClickHouse.
Ease of Deployment and Customer Service: PostgreSQL is easy to deploy across multiple platforms, including cloud environments, driven by a strong community and extensive resources. ClickHouse offers flexible deployment with a focus on on-premise and cloud settings. Despite its active user community, improving documentation and simplifying on-premise setups could enhance ClickHouse's user support experience.
Pricing and ROI: Both PostgreSQL and ClickHouse are open-source, offering significant savings by eliminating licensing fees. PostgreSQL provides a strong ROI due to its zero licensing costs and multi-platform compatibility, making it appealing for startups and scalable enterprise solutions. ClickHouse is cost-effective for on-premise scenarios due to its competitive pricing and flexibility, particularly for businesses seeking cost-efficient high-performance analytics.
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%.
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.
If PostgreSQL is hosted on cloud services such as Amazon RDS or Google Cloud SQL, the support is handled by the cloud provider, who provides automated backups, monitoring, infrastructure management, and technical support tickets.
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.
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.
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.
Query optimization improves slow queries by using proper indexes, avoiding unnecessary joins, and using EXPLAIN ANALYZE to inspect query plans.
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.
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.
PostgreSQL improves reliability, performance, and scalability in production. Since it is ACID compliant, it ensures that database transactions are safe and consistent, preventing partial data updates, maintaining data integrity, and allowing multiple users to read or write data simultaneously using MVCC.
| Product | Mindshare (%) |
|---|---|
| PostgreSQL | 14.4% |
| ClickHouse | 6.6% |
| Other | 79.0% |

| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 4 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 57 |
| Midsize Enterprise | 27 |
| Large Enterprise | 46 |
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.
PostgreSQL is a versatile and reliable database management system commonly used for web development, data analysis, and building scalable databases.
It offers advanced features like indexing, replication, and transaction management. Users appreciate its flexibility, performance, and ability to handle large amounts of data efficiently. Its robustness, scalability, and support for complex queries make it highly valuable.
Additionally, PostgreSQL's extensibility, flexibility, community support, and frequent updates contribute to its ongoing improvement and stability.
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