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Apache Kylin

45
164
+ 1
23
Druid

264
550
+ 1
26
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Apache Kylin vs Druid: What are the differences?

Developers describe Apache Kylin as "OLAP Engine for Big Data". Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc. On the other hand, Druid is detailed as "Fast column-oriented distributed data store". Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Apache Kylin and Druid can be categorized as "Big Data" tools.

Apache Kylin and Druid are both open source tools. It seems that Druid with 8.22K GitHub stars and 2.05K forks on GitHub has more adoption than Apache Kylin with 2.21K GitHub stars and 983 GitHub forks.

Pros of Apache Kylin
Pros of Druid
  • 7
    Star schema and snowflake schema support
  • 5
    Seamless BI integration
  • 4
    OLAP on Hadoop
  • 3
    Sub-second latency on extreme large dataset
  • 2
    Easy install
  • 2
    ANSI-SQL
  • 13
    Real Time Aggregations
  • 4
    OLAP
  • 4
    Batch and Real-Time Ingestion
  • 2
    Combining stream and historical analytics
  • 2
    OLAP + OLTP
  • 1
    OLTP

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Cons of Apache Kylin
Cons of Druid
    Be the first to leave a con
    • 2
      Limited sql support
    • 1
      Complexity
    • 1
      Joins are not supported well

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    What is Apache Kylin?

    Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

    What is Druid?

    Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

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    What companies use Apache Kylin?
    What companies use Druid?

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    What tools integrate with Apache Kylin?
    What tools integrate with Druid?

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    What are some alternatives to Apache Kylin and Druid?
    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.
    Presto
    Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
    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.
    AtScale
    Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.
    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.
    See all alternatives
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