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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    ClickHouse

    Score7 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

    MonetDB

    Score7 out of 10
    N/AMonetDB is an open source column-oriented relational database management system issued and supported by the Dutch MonetDB development team.N/A
    Pricing
    ClickHouseMonetDB
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    ClickHouseMonetDB
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsPay 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
    ClickHouseMonetDB
    Small Businesses
    SingleStore
    Score7.5 out of 10
    SingleStore
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    Medium-sized Companies
    SAP HANA Cloud
    Score8.9 out of 10
    SAP HANA Cloud
    Score8.9 out of 10
    Enterprises
    SAP IQ
    Score10 out of 10
    SAP IQ
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    All AlternativesView all alternativesView all alternatives
    User Ratings
    ClickHouseMonetDB
    Likelihood to Recommend
    10.0
    (2 ratings)
    7.0
    (2 ratings)
    User Testimonials
    ClickHouseMonetDB
    Likelihood to Recommend
    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.
    Incentivized
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    MonetDB
    MonetDB is great when you are performing adhoc queries on a large set of data. For example, if you store data in a typical RDBMS such as MySQL or Postgres and want to join large tables for analytics but the query runs unacceptably slow then MonetDB can act as a second database to offload complex queries. Based on my experience, it may not be a production-ready database since there aren't many DBAs familiar with it and due to lack of documentation, maintenance can become a little tricky.
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    Pros
    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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    MonetDB
    • It is easy to use.
    • You are able to input lots of data and it understands and populates information.
    • Able to change settings on the fly to use with your needs.
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    Cons
    ClickHouse, Inc.
    • Avro data manipulation
    • Kafka consistency
    • DDL operations errors (by replica configuration)
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    MonetDB
    • This is an open source software so there are obvious drawbacks, the biggest of which is a lack of documentation.
    • MonetDB does not seem to be well known outside of the academic environment so there is less information when you are searching for answers of any type.
    • I'd like to see more use cases and/or best practices so that commercial companies like ours can optimally use all of its highly performant features.
    • The code is written in C/C++ and this can be negative if you are a mainly java-shop and need UDF - User Defined Function.
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    Alternatives Considered
    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.
    Incentivized
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    MonetDB
    We have used Five9 in my previous company but on a much smaller scale. It was more expensive, however we were using it for a max of 50 employees, now we need a much bigger platform. We also used Five9 for other things, like phone dialers etc. so it was a little different.
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    Return on Investment
    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
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    MonetDB
    • If you are familiar with a general database concept and played with open source products before then MonetDB will give you immediate return in terms of productivity since developers can quickly develop and verify their test cases involving back-end database with a large sample data set.
    • There is a stiff learning curve due to lack of documentation and sparse information available on the internet.
    • Overall experience has been positive since MonetDB gives you another option when it comes to building out a data warehouse.
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