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Clickhouse vs Scylla: What are the differences?
Developers describe Clickhouse as "A column-oriented database management system". It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query. On the other hand, Scylla is detailed as "Next Generation Cassandra". Real-time big data database, with scale-up performance of 1,000,000 IOPS per node, scale-out to 100s of nodes and 99 latency of less than 1 msec.
Clickhouse and Scylla belong to "Databases" category of the tech stack.
Scylla is an open source tool with 5.25K GitHub stars and 619 GitHub forks. Here's a link to Scylla's open source repository on GitHub.
According to the StackShare community, Clickhouse has a broader approval, being mentioned in 22 company stacks & 11 developers stacks; compared to Scylla, which is listed in 16 company stacks and 6 developer stacks.
The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.
The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.
By 55M do you mean 55 million entity changes per 2 minutes? It is relatively high, means almost 460k per second. If I had to choose between Scylla or Cassandra, I would opt for Scylla as it is promising better performance for simple operations. However, maybe it would be worth to consider yet another alternative technology. Take into consideration required consistency, reliability and high availability and you may realize that there are more suitable once. Rest API should not be the main driver, because you can always develop the API yourself, if not supported by given technology.
Cassandra is quite capable of the task, in a highly available way, given appropriate scaling of the system. Remember that updates are only inserts, and that efficient retrieval is only by key (which can be a complex key). Talking of keys, make sure that the keys are well distributed.
Scylla can handle 1M/s events with a simple data model quite easily. The api to query is CQL, we have REST api but that's for control/monitoring
i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra
The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:
We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.
Pros of Clickhouse
- Fast, very very fast19
- Good compression ratio11
- Horizontally scalable6
- Great CLI5
- RESTful5
- Utilizes all CPU resources5
- Open-source4
- Great number of SQL functions4
- Has no transactions3
- Buggy3
- Server crashes its normal :(2
- ODBC2
- Flexible connection options2
- Flexible compression options2
- Highly available2
- In IDEA data import via HTTP interface not working1
Pros of ScyllaDB
- Replication2
- Fewer nodes1
- Distributed1
- Scale up1
- High availability1
- Written in C++1
- High performance1
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Cons of Clickhouse
- Slow insert operations5
