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Apache Kudu

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Pros of Apache Kudu
Pros of Clickhouse
  • 10
    Realtime Analytics
  • 19
    Fast, very very fast
  • 11
    Good compression ratio
  • 6
    Horizontally scalable
  • 5
    Great CLI
  • 5
  • 5
    Utilizes all CPU resources
  • 4
  • 4
    Great number of SQL functions
  • 3
    Has no transactions
  • 3
  • 2
    Server crashes its normal :(
  • 2
  • 2
    Flexible connection options
  • 2
    Flexible compression options
  • 2
    Highly available
  • 1
    In IDEA data import via HTTP interface not working

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Cons of Apache Kudu
Cons of Clickhouse
  • 0
    Restart time
  • 5
    Slow insert operations

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What is Apache Kudu?

A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

What is Clickhouse?

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.

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What companies use Apache Kudu?
What companies use Clickhouse?
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What tools integrate with Apache Kudu?
What tools integrate with Clickhouse?

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What are some alternatives to Apache Kudu and Clickhouse?
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Apache Impala
Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
See all alternatives