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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Cassandra

    Score9 out of 10
    N/ACassandra is a no-SQL database from Apache.N/A

    ClickHouse

    Score7.3 out of 10
    N/AClickHouse is an open-source, column-oriented OLAP database system enabling real-time analytical reports using SQL queries. With linear scalability, it handles trillions of rows and petabytes of data. ClickHouse Cloud offers a scalable serverless solution for real-time analytics.N/A
    Pricing
    CassandraClickHouse
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    CassandraClickHouse
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—Pay for what is used: It automatically scales up and down compute resources based on the user's workload It scales storage and compute separately It automatically scales unused resources down to zero so that users don’t pay for idle services
    More Pricing Information
    Best Alternatives
    CassandraClickHouse
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    HBase
    Score7.3 out of 10
    Snowflake
    Score8.7 out of 10
    Enterprises
    Azure Cosmos DB
    Score9.1 out of 10
    Snowflake
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    CassandraClickHouse
    Likelihood to Recommend
    6.0
    (16 ratings)
    10.0
    (2 ratings)
    Likelihood to Renew
    8.6
    (16 ratings)
    -
    (0 ratings)
    Usability
    7.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    7.0
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    7.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    CassandraClickHouse
    Likelihood to Recommend
    Apache
    Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
    Incentivized
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    ClickHouse, Inc.
    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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    Pros
    Apache
    • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
    • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
    • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
    • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
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    ClickHouse, Inc.
    • 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
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    Cons
    Apache
    • Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
    • Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
    • There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
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    ClickHouse, Inc.
    • Avro data manipulation
    • Kafka consistency
    • DDL operations errors (by replica configuration)
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    Likelihood to Renew
    Apache
    I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
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    ClickHouse, Inc.
    No answers on this topic
    Usability
    Apache
    It’s great tool but it can be complicated when it comes administration and maintenance.
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    ClickHouse, Inc.
    No answers on this topic
    Support Rating
    Apache
    Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
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    ClickHouse, Inc.
    No answers on this topic
    Alternatives Considered
    Apache
    We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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    ClickHouse, Inc.
    ClickHouse outperforms, especially in costs, since its compression/indexing engines are so smart, and even with very low computing power, you can already perform huge analyses of the data.
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    Return on Investment
    Apache
    • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
    • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
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    ClickHouse, Inc.
    • 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
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