ClickHouse

ClickHouse

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Score 9.3 out of 100
ClickHouse

Overview

What is ClickHouse?

ClickHouse is an open-source column-oriented database management system developed at Yandex, that manages large volumes of data, including non-aggregated data, and allows generating custom data reports in real time. The system is linearly scalable and can be scaled up to...
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What is ClickHouse?

ClickHouse is an open-source column-oriented database management system developed at Yandex, that manages large volumes of data, including non-aggregated data, and allows generating custom data reports in real time. The system is linearly scalable and can be scaled up to store and process trillions…

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Product Details

What is ClickHouse?

ClickHouse is an open-source column-oriented database management system developed at Yandex, that manages large volumes of data, including non-aggregated data, and allows generating custom data reports in real time. The system is linearly scalable and can be scaled up to store and process trillions of rows and petabytes of data.

ClickHouse Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Reviews and Ratings

 (5)

Reviews

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Score 9 out of 10
Vetted Review
Verified User
In essence, ClickHouse DB is column-oriented, and whenever we do query a large collection of data, we get a result in a shorter period of time. As a result, we are able to retrieve millions of records in a short period of time, allowing us to analyze the data much more quickly. A nice compression algorithm on Clickhouse makes our software/application easier to dump data into a database and retrieve the data to display. There are so many problems, but I want to highlight one. For example, we have faced a problem with dumping a lot of data and need to run a bunch of queries in five minutes, so ClickHouse is the only way to scale heavy data quickly. Moreover, it helps aggregate data in real-time. Business Problem: There were so many problems we faced, but I want to highlight one. For example, we have faced a problem with dumping a lot of data and need to run a bunch of queries in five minutes, so click-house is the only way to scale heavy data quickly. Moreover, it helps aggregate data in real-time.
  • Column-oriented
  • Horizontally scale possible
  • Work efficiently with huge amount of data
  • Query language is so easy just like SQL
  • Unable to make custom functions
  • So many times it required to use multiple joins
  • I faced a lot of problems with Zookeeper, Partitioning, Sharding, and replication.
1) An extensive SQL syntax. A lot of functions are included (including GeoDistances, Uber Hexagons, time functions, comprehensive Mah, and many others). Several functions can be combined (e.g. SumIf, AvgIf, etc.) which is very convenient.
2) It is quick. The arrays and MapReduce make CH work lightning fast. I was extremely surprised when several GBs of data were processed in less than a second.
3)A fast response time. Using Materialized Views correctly allows instant processing of TBs of data, which works differently than in other databases.
4)This is an efficient process. It is possible to store data extremely efficiently by using a wide range of data types and compression algorithms. Choose the best compression type for your tables based on the documentation. There will be a lot of surprises for you.
Score 9 out of 10
Vetted Review
Verified User
ClickHouse is used to carry out analysis tasks that traditional databases are not capable of performing, either because they are too expensive or because the volume of data is so large that it is not feasible to analyze it with queries comfortably. The analysis of indicators on which aggregations are needed but not on the rest of the indicators that are stored together in the same traditional table is one of the biggest problems that ClickHouse solves, making the queries run very fast with hardware that is not as advanced as it would be for a traditional table.
  • Opensource
  • High performance
  • Multiple engines to adapt user cases
  • Easy configuration of data replication
  • Avro data manipulation
  • Kafka consistency
  • DDL operations errors (by replica configuration)
The most important thing when using ClickHouse is to be clear that the scenarios in which you want to use it really are the right ones. Many users think that when a database is very fast for a specific use case, it can be extrapolated to other contexts (most of the time different) in which a previous analysis has not been carried out.

ClickHouse is an analytical database, as such, it should be used for such purposes, where the information is stored correctly, the data volumes are really large and the queries to be performed are not the typical traditional queries on several columns with multiple aggregations. ClickHouse is not the solution for this.

On the other hand, if your case is not one of the above, it is quite possible that ClickHouse can help you. Where ClickHouse shines is when you are looking for aggregation over a particular column in large volumes of data.
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