I do not use the tool myself. Our developers and data analysts use it.
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A flexible solution with good documentation and integration
What is our primary use case?
What is most valuable?
The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility. While it may not be the best on the market, it is the best open-source solution we have tried. It has a development community and good documentation, though not all is published.
The tool's integration with other tools is not complex. We use it alongside Kafka and Tableau.
For how long have I used the solution?
I have been using the product for four years.
What do I think about the scalability of the solution?
Every customer I've worked with over the past few years uses ClickHouse, including many Russian companies and those related to Russia.
How are customer service and support?
I have some experience talking with the tech support team. It was an open-source project at one point, so I used community resources for help. The best way to communicate with them was through their program channel, which had support available in both English and Russian.
How was the initial setup?
Regarding the initial installation, setup, and deployment, I can say it's easy for someone with my engineering skills. I prefer managing the installation myself rather than relying on out-of-the-box solutions.
What other advice do I have?
ClickHouse is good for analytics. Using ClickHouse is beneficial if you understand its specific purpose and advantages. Many engineers and developers mistakenly think it is an alternative to AWS databases like Postgres or MySQL, but it's not. ClickHouse has a different architecture and purpose, primarily excelling at analytical queries rather than traditional CRUD operations.
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. As an infrastructure engineer, it shouldn't be hard either.
I rate the overall solution an eight out of ten.
Which deployment model are you using for this solution?
On-premises
Query engine is super fast but improvement needed in integration to third-party applications or the cloud
What is our primary use case?
Our use cases are for data analytics, both real-time and batch, and also for logging Clickstream data.
We use it in our organization. We have it in our production environment.
What is most valuable?
The query engine is super fast. We deploy ClickHouse on our Kubernetes cluster, not as a cloud subscription, so it's easy to scale with the deployment.
What needs improvement?
Some features, like connecting to third-party applications or the cloud, could be better.
For how long have I used the solution?
I have been using it for one year.
What do I think about the stability of the solution?
One issue is that you need persistent volumes. Otherwise, if one system goes down, you lose data in that cluster.
Another issue is performance. You have to make sure you have the right configurations; otherwise, it will lead to queuing where all your jobs get queued.
What do I think about the scalability of the solution?
It is a scalable product.
How are customer service and support?
You only get technical support when you take the cloud subscription. If you have it in-house, you won't get any support. If you have a cloud subscription, then the support is pretty good. You can raise a ticket from the UI, and they will respond within 24 hours.
So, the support team is pretty good but there is a little room for improvement.
How would you rate customer service and support?
Neutral
How was the initial setup?
The initial setup is pretty difficult since we deployed it in-house. We didn't use the cloud subscription, so we have to handle the deployment very carefully.
The challenge was deploying it and having the replication concept working. Another challenging feature is persistent volumes. You have to make sure the data is available on all clusters; otherwise, if one cluster goes down, you'll lose all your data. It's better to have it replicated.
We first used the cloud subscription, but we saw a possibility to reduce costs, so we tried deploying the open-source ClickHouse on-premises. That saved us money, but we didn't get all the features that come with the subscription.
What about the implementation team?
We did it in-house.
What's my experience with pricing, setup cost, and licensing?
Pricing for the cloud version is alright, not very costly or cheap.
But if you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything.
What other advice do I have?
I would tell other users to do a POC because it depends upon the business use case and the data. They can explore first. There's another open-source option called Apache Druid, which is a little better than ClickHouse. If that doesn't fit the use case, then they could go for ClickHouse.
Overall, I would rate the solution a seven out of ten.
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. So, if your use case is real-time or logging or real-time dashboarding, then ClickHouse is a tool to consider. Otherwise, if it's batch processing and you can expect some latency, then you should go for other databases.
Which deployment model are you using for this solution?
Hybrid Cloud
If ClickHouse was a car it would be the Lightning McQueen of data.
What do you like best about the product?
Everyone knows that ClickHouse is the fastest database on the planet, massively reducing the hardware footprint to $100 for most projects. But what makes it shine is the enormous range of procedural functions that can be intertwined with the SQL, which bridge scripting with query negating repetitive queries altogether and allowing itterative, selective and extrapolative access to extended field formats such as complex structures. Finally, the materialised view pre-calculates an abstracted table in the background. All around, it's incredible.
What do you dislike about the product?
There are no significant drawbacks except a slight learning curve when you get started, but as standard SQL works fine, the transition into more complex queries is painless, and the documentation helps a lot.
What problems is the product solving and how is that benefiting you?
Querying billions of records on a $100 device and speed benefit me the most.
Strongest and Powerful DB for large scale of data analysis
What do you like best about the product?
Basically, clickhouse DB is column-oriented and so whenever we are using a query to fetch a huge amount of data it provides a result in less time. it's so amazing as we can quicky retrive the millions of records to analyze the data. Clickhouse having a nice compression algorithm which makes software easier with dumping the data into a database and retrieving the data to show at GUI.
What do you dislike about the product?
I guess so far I do not find any of but in some points, I got the updates as it's in pipeline for development but need to highlight one thing as sometimes unable to get the actual answers from the forum hence I would say it's time-consuming for getting the resolution
What problems is the product solving and how is that benefiting you?
so many problems but would like to highlight one which is like We have faced an issue with dumping a huge amount of data and would like to call a bunch of queries in 5 minutes and in that case click-house is the only way to scale any number of huge data to get a quick result. In addition, it helps with the real-time aggregation of data.
Recommendations to others considering the product:
Yes, I would suggest who deals with a huge amount of data and is required to get all the results as much as quickly then definitely go with clickhouse DB. It helps with getting data about analytical results for web applications.
Great data store solution for large data analytics
What do you like best about the product?
Very fast when it comes to querying large amounts of data.
The count operation in specific is super quick.
The count operation in specific is super quick.
What do you dislike about the product?
It is a lot of work if you want to edit any value that is already stored in the database.
What problems is the product solving and how is that benefiting you?
We add billions of records to it every day and use different materialized views to gather various analytics.
The read time and processing are very optimal compared to other solutions.
It compresses and stores data and that saves a lot of disk space.
The read time and processing are very optimal compared to other solutions.
It compresses and stores data and that saves a lot of disk space.
Clickhouse is a very good OLAP base system work more efficiently then any RDBMS like MYSQL.
What do you like best about the product?
The functionality of solving various problems is effortless, what is have found in the clickhouse most appealing
What do you dislike about the product?
As of now, Nothing I dislike about click house.
What problems is the product solving and how is that benefiting you?
Various problems I have solved like intent creation, high-speed calculations, and much more
Over 100 billion records in my hands
What do you like best about the product?
I like good data compression and fast query execution
What do you dislike about the product?
I dislike upgrade issues from v.19 to v.21
What problems is the product solving and how is that benefiting you?
Fast query results over billions of records, storage savings with data compression
Recommendations to others considering the product:
I would recommend clickhouse for big data analytics
Clickhouse does a lot of things right and but it still not stable for production use.
What do you like best about the product?
Perfom and huge arsenal of Engines that helps you ingest and process data at scale.
Like they have an Engine for almost all use case.
Like they have an Engine for almost all use case.
What do you dislike about the product?
Stability and predictability. Clickhouse despite it's huge advantages sometimes doesn't provide you with the stability and behaviour needed for a production system.
What problems is the product solving and how is that benefiting you?
Bulk data ingestion and Big data analysis
Recommendations to others considering the product:
The documents are sometimes outdated and there isn't a huge community support out there. For a production system that needs absolute reliance, I won't recomend.
The fastest and most powerful DB ever used
What do you like best about the product?
TLDR:
Fast, Very Very Very Fast, Rich SQL, Good compression algorithms
Detail:
1) Rich SQL syntax. There are a lot of in-build functions (including GeoDistances, Uber Hexagons support, time functions, comprehensive mah, and many others). Functions could be combined (e.g. with If: SumIf, AvgIf, etc) which is very convenient.
2) Fast. Arrays and MapReduce make CH working LIGHTNING FAST. I was extremely surprised when several GBs of data were processed in under 1 second.
3) Fast. Materialized Views work differently than in other databases, but the correct usage allows instant processing of TBs of data.
4) Efficient. Vast amount of data types and compression algorithms help you to store data extremely efficiently. Make sure to check the docs and choose the best compression types for your tables. You will be very surprised.
Overall you see very smart engineers worked on this database. It was made by engineers for engineers.
Fast, Very Very Very Fast, Rich SQL, Good compression algorithms
Detail:
1) Rich SQL syntax. There are a lot of in-build functions (including GeoDistances, Uber Hexagons support, time functions, comprehensive mah, and many others). Functions could be combined (e.g. with If: SumIf, AvgIf, etc) which is very convenient.
2) Fast. Arrays and MapReduce make CH working LIGHTNING FAST. I was extremely surprised when several GBs of data were processed in under 1 second.
3) Fast. Materialized Views work differently than in other databases, but the correct usage allows instant processing of TBs of data.
4) Efficient. Vast amount of data types and compression algorithms help you to store data extremely efficiently. Make sure to check the docs and choose the best compression types for your tables. You will be very surprised.
Overall you see very smart engineers worked on this database. It was made by engineers for engineers.
What do you dislike about the product?
TLDR:
You gotta read docs first. Requires Zookeeper.
Detail:
1) I faced a lot of problems with Zookeeper, Partitioning, Sharding, and replication.
2) Learning is not that easy, but it worth it.
You gotta read docs first. Requires Zookeeper.
Detail:
1) I faced a lot of problems with Zookeeper, Partitioning, Sharding, and replication.
2) Learning is not that easy, but it worth it.
What problems is the product solving and how is that benefiting you?
We had a lot of data coming from devices permanently (with around 50 Hz frequency). All this data had to be stored and processed.
CH allowed us to store efficiently and process in real time. It's very fast.
CH allowed us to store efficiently and process in real time. It's very fast.
Recommendations to others considering the product:
Make sure to spend a few hours in the docs first and especially learn about Arrays. Thank me later.
A Column-oriented Database which is blazingly fast.
What do you like best about the product?
Clickhouse is a column-oriented DBMS, and it is fault-tolerant and blazingly fast. Sql like syntax makes it super easy to use. The mathematics using behind scenes using vectors and merging algorithms gives the power to it. I like how quickly we can retrieve the data from the database. In Analytics/Reports we require to get/insert the millions of records and Clickhouse fulfills the purpose. Since it is a column-oriented DBMS, it performs things quickly.
What do you dislike about the product?
I disliked the fact there I can't make custom functions, I want that in Clickhouse so that we can form our own functions and use them. Materialized Views are still a mystery here they are super valuable but sometimes it tedious to use them and really required multiple joins in materialized views, currently, it's supporting only a single join which is not fulfilling the purpose sometimes. Clickhouse should introduce triggers since materialized views are not helping much here.
What problems is the product solving and how is that benefiting you?
I have been using Clickhouse for reporting in my company. Previously we were using MySQL, and retrieval for half a million was taking 5-10 min there while after using Clickhouse it took only seconds. Clickhouse is really useful when it comes to reporting since there we have to retrieve the huge data and perform transformations, its mysql like syntaxes are super useful that takes no time to adapt this. There are many supportive engines like mergetree, collapsingtree, and engines helping to interact with other dbs like mysql are really useful.
Recommendations to others considering the product:
If dealing with analytics, then this one is a must-try.
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