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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    ClickHouse

    Score7.2 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

    IBM Analytics Engine

    Score7.1 out of 10
    N/AIBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
    Pricing
    ClickHouseIBM Analytics Engine
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    ClickHouseIBM Analytics Engine
    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
    ClickHouseIBM Analytics Engine
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    Snowflake
    Score8.7 out of 10
    Cloudera Manager (no longer available standalone)
    Score9.9 out of 10
    Enterprises
    Snowflake
    Score8.7 out of 10
    Hadoop
    Score7.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    ClickHouseIBM Analytics Engine
    Likelihood to Recommend
    10.0
    (2 ratings)
    9.5
    (9 ratings)
    User Testimonials
    ClickHouseIBM Analytics Engine
    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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    IBM
    • Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
    • But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.
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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
    Incentivized
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    IBM
    • Jobs with Spark, Hadoop, or Hive queries are rapidly attained
    • Can collect, organize and analyze your data accurately
    • You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries.
    Incentivized
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    Cons
    ClickHouse, Inc.
    • Avro data manipulation
    • Kafka consistency
    • DDL operations errors (by replica configuration)
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    IBM
    • Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
    • Bundling of the Cloud Object Storage should be included with the Analytics Engine.
    • The inability to add your own Hadoop stack components has made some transfers a little more complex.
    Incentivized
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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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    IBM
    We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.
    Incentivized
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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
    Incentivized
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    IBM
    • This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
    • IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
    • The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.
    Incentivized
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