ClickHouse vs Microsoft Azure Cosmos DB comparison

"The tool is column-based and infinitely scalable."

"ClickHouse is much faster than traditional databases like MySQL and MongoDB. Its column-row searching strategy makes it very efficient. With ClickHouse, we can manage multiple databases, automatically insert data from other databases and delete data as needed. It supports real-time query performance, allowing simultaneous data insertion and retrieval. ClickHouse has improved significantly over the past two years, adding more functions and queries, as well as top functionality."

"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."

"We faced a challenge with deploying ClickHouse onto Kubernetes. Recently, we've been using ClickHouse Cloud, and the main issue is the high cost of the cloud service. The pricing isn't very competitive, especially for startups. I would instead buy a server and self-host if I have enough disk space. Besides that, ClickHouse has done very well, with clear goals and effective execution."

"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."

"It's easier to work with big data and calculations using the product."

"The best thing about the tool is that I can set it up on my computer and run queries without depending on the cloud. This is why I use it every day."

"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 one of the simpler databases to work with in terms of code management, tracking, and debugging due to its straightforward data storage and retrieval mechanisms."

"It gives us a lot of flexibility. The scaling is instantaneous as well. You immediately have all the resources available."

"The solution is user friendly and Microsoft's technical support is good."

"The product has a lot of useful features that are there and ready to use, it's also very easy to use."

"What I like about Microsoft Azure Cosmos DB is that it's easy to do data ingestion and use the data in different applications. If you talk about business intelligence such as the Power BI tool, it's easy to connect because both are Microsoft products. With Microsoft Azure Cosmos DB, it's easy to connect and do data ingestion."

"From a global distribution perspective, Microsoft Azure Cosmos DB is good and easy to handle."

"Cosmos DB makes life easier because if we want to use Mongo-type data, or Cassandra-type data, or maybe even just a simple cable storage-type data, then graph, there are multiple ways to do this."

"One of the nice features is the ability to auto-scale"

"We had a lot of troubles while deploying a whole cluster."

"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."

"If you join our team, it should be easy for you to use ClickHouse, especially if you are a developer. However, you need to read the documentation and understand the problems you are trying to solve."

"There aren't too many improvements I'd suggest for ClickHouse as it covers all my needs. There are just a few technical issues. For example, sometimes, when you want to get unique values and use certain tables, they don't work as expected. But it's not a major problem."

"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."

"The aggregation capability is a valuable feature. It's highly efficient, allowing us to review entire transaction histories and user activities in the market. We've tried MongoDB, Postgres, MariaDB, and BigQuery, but ClickHouse is the most cost-efficient solution for collecting data at high speeds with minimal cost. We even used ClickHouse Cloud for a month, and it proved to be a great setup, especially for startups looking to handle big data. For example, if there is a need for 2-4 terabytes of data and around 40 billion rows with reasonable computing speed and latency, ClickHouse is ideal. Regarding the real-time query performance of ClickHouse, when using an API server to query it, I achieved query results in less than twenty milliseconds in some of my experiments with one billion rows. However, it depends on the scenario since ClickHouse has limitations in handling mutations. Additionally, one of ClickHouse's strengths is its compression capability. Our experimental server has only four terabytes, and ClickHouse effectively compresses data, allowing us to store large amounts of data at high speed. This compression efficiency is a significant advantage of using ClickHouse."

"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."

"One issue is that you need persistent volumes. Otherwise, if one system goes down, you lose data in that cluster."

"We should have more freedom to tweak it and make our own queries for non-traditional use-cases."

"There is room for improvement in their customer support services."

"There is room for improvement in terms of stability."

"It should offer a simple user interface for querying Microsoft Azure Cosmos DB."

"Microsoft Azure Cosmos DB's pricing model is complicated, which people don't understand."

"I hope they improve the service. Before last year, improvements on Cosmos DB were very slow."

"While Microsoft Azure Cosmos DB is generally easy to use, it has some limitations."

"The solution cannot join two databases like Oracle or SQL Server."

"ClickHouse has an open-source version, which is free to use and has almost all the features."

"The tool is free."

"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."

"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."

"The tool is open-source."

"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."

"We used the free, community version of ClickHouse."

"Right now, I have opted for the student subscription plan, for which Microsoft charges me around 100 USD. The pricing of the solution depends on the solution's usage."

"Cosmos DB is a PaaS, so there are no upfront costs for infrastructure. There are only subscriptions you pay for Azure and things like that. But it's a PaaS, so it's a subscription service. The license isn't perpetual, and the cost might seem expensive on its face, but you have to look at the upkeep for infrastructure and what you're saving."

"The price of Microsoft Azure Cosmos DB could be a bit lower."

"With heavy use, like a large-scale IoT implementation, you could easily hit a quarter of a million dollars a month in Azure charges if Cosmos DB is a big part of it."

"The solution is a bit on the expensive side."

"Pricing is one of the solution's main features because it is based on usage, scales automatically, and is not too costly."

"The Cosmos DB pricing model, initially quite complicated, became clear after consulting with Azure Advisor, allowing us to proceed with confidence."

"The solution is very expensive."