

Microsoft Azure Cosmos DB and ClickHouse compete in the database management space. Based on the data comparisons, Microsoft Azure Cosmos DB appears to have an edge due to its comprehensive global distribution features and dynamic performance enhancements.
Features: Microsoft Azure Cosmos DB offers robust global distribution capabilities, serverless mode for improved performance, and extensive API support facilitating platform integration. ClickHouse focuses on fast query performances, efficient data compression, and effective column-row searching strategies ideal for large-scale analytics.
Room for Improvement: Microsoft Azure Cosmos DB faces challenges with partition management, expensive vector search pricing, and complex RU consumption models. ClickHouse requires enhanced documentation, better third-party integration, and simplified cluster deployment processes.
Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB is easily deployed across various cloud environments with mixed regional customer service experiences. ClickHouse, typically hosted on-premises or in private clouds, relies on community-driven forums for support, though official support varies.
Pricing and ROI: Microsoft Azure Cosmos DB's pricing is perceived as complex due to its Request Unit model but aligns well with resource management benefits. In contrast, ClickHouse offers cost-effective deployment through open-source availability, especially for large-scale projects when self-hosted.
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%.
Getting an MVP of that project would have taken six to eight months, but because we had an active choice of using Azure Cosmos DB and other related cloud-native services of Azure, we were able to get to an MVP stage in a matter of weeks, which is six weeks.
You can react quickly and trim down the specs, memory, RAM, storage size, etc. It can save about 20% of the costs.
When I have done comparisons or cost calculations, I have sometimes personally seen as much as 25% to 30% savings.
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.
Premier Support has deteriorated compared to what it used to be, especially for small to medium-sized customers like ours.
The response was quick.
I would rate customer service and support a nine out of ten.
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 system scales up capacity when needed and scales down when not in use, preventing unnecessary expenses.
We like that it can auto-scale to demand, ensuring we only pay for what we use.
We have had no issues with its ability to search through large amounts of data.
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.
We have multiple availability zones, so nothing goes down.
Azure Cosmos DB would be a good choice if you have to deploy your application in a limited time frame and you want to auto-scale the database across different applications.
I would rate it a ten out of ten in terms of availability and latency.
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.
We must ensure data security remains the top priority.
You have to monitor the Request Units.
The dashboard could include more detailed RU descriptions, IOPS, and compute metrics.
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.
Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective.
Cosmos DB is expensive, and the RU-based pricing model is confusing.
Cosmos DB is great compared to other databases because we can reduce the cost while doing the same things.
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 valuable feature of Microsoft Azure Cosmos DB is its real-time analytics capabilities, which allow for turnaround times in milliseconds.
Performance and security are valuable features, particularly when using Cosmos DB for MongoDB emulation and NoSQL.
The performance and scaling capabilities of Cosmos DB are excellent, allowing it to handle large workloads compared to other services such as Azure AI Search.
| Product | Market Share (%) |
|---|---|
| Microsoft Azure Cosmos DB | 5.8% |
| ClickHouse | 4.7% |
| Other | 89.5% |

| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 4 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 21 |
| Large Enterprise | 58 |
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.
Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.
Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.
What are the key features of Azure Cosmos DB?Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.
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