ClickHouse vs. VictoriaMetrics Community

ClickHouse delivers exceptional speed and performance, positioning it as the top choice for managing large-scale analytical workloads. With a bunch of built-in functions, it empowers analysts to extract maximum insights from data effortlessly. If your scenario is to deal with analytical questions, then ClickHouse is for you, but if you are looking into a transactional database, that's not the case; even their table engines are not made for this.

Incentivized

1. It is well suited when you need to monitor large scale of metrics as compared to Prometheus it is faster,more reliable and can provide you metric for more retention period. 2. Uses less resource to run application , can easily be containerised 3. It supports both push and pull models and can be intergated with multiple alerting systems

Incentivized

• Their MergeTree table engine provide impressive performance for data insert in bulk
• Not only data insert but also the way MergeTree engine uses Primary Keys to sort the data and perform data skipping based on the granules its also their secret for ridiculous fast queries
• Data compression its also great
• They provide especial table engines that allow you to read data directly from other sources like S3
• Since its written with C++ you have very granular data types and especial ones like enum, LowCardinality and etc, they save you a lot of storage since are stored as integer values
• ClickHouse functions besides the ones that respect ANSI Standards are also awesome and useful

Incentivized

• Easy to configure and manage
• Ready to be configured at cloud and microservices
• Easy to scale vertically and horizontally

Incentivized

• Avro data manipulation
• Kafka consistency
• DDL operations errors (by replica configuration)

Incentivized

• Community and Eco system -> Although it supports the ecosystem of Prometheus, it is still troublesome for someone who's not using Prometheus
• Configuration is not so easy, especially if you are a beginner, you will struggle a bit. Even the documentation is not so welcoming for beginners
• Built-in Visualisation is bare minimal, leading almost everyone to use some other extension/tool

Incentivized

ClickHouse was not compared to them as a competitor but as the ideal partner to complete an information analysis system, providing users with the most complete and efficient tools. Therefore, in this case it was considered that it would be the ideal candidate due to its characteristics compared to the other competitors.

Incentivized

Victoria metrics is cheaper and more efficient than Prometheus, in terms of data ingestions, hardware resources, and Storage mechanism, also supports Prometheus extensions, and query language by default. Although Prometheus has a larger community and support, because of the interoperability of Victoria metrics the difference wouldn't concern us much. At the same time, it made our migration simpler

Incentivized

• Queries that used to take more than 2 minutes now take less than 1 second
• Possibility to analyze use cases in real time (before was impossible)
• The applications are more complete and the users decisions are better

Incentivized

• Lowered our infra costs in comparison with our older tools
• Need minimal effort for migration since it already supports Prometheus ecosystem
• Saved on Storage costs

Incentivized