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Clickhouse

340
477
+ 1
76
Druid

364
828
+ 1
31
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Clickhouse vs Druid: What are the differences?

Clickhouse: A column-oriented database management system. 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; Druid: 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.

Clickhouse can be classified as a tool in the "Databases" category, while Druid is grouped under "Big Data Tools".

Druid is an open source tool with 8.32K GitHub stars and 2.08K GitHub forks. Here's a link to Druid's open source repository on GitHub.

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Pros of Clickhouse
Pros of Druid
  • 19
    Fast, very very fast
  • 11
    Good compression ratio
  • 6
    Horizontally scalable
  • 5
    Great CLI
  • 5
    RESTful
  • 5
    Utilizes all CPU resources
  • 4
    Open-source
  • 4
    Great number of SQL functions
  • 3
    Has no transactions
  • 3
    Buggy
  • 2
    Server crashes its normal :(
  • 2
    ODBC
  • 2
    Flexible connection options
  • 2
    Flexible compression options
  • 2
    Highly available
  • 1
    In IDEA data import via HTTP interface not working
  • 15
    Real Time Aggregations
  • 6
    Batch and Real-Time Ingestion
  • 4
    OLAP
  • 3
    OLAP + OLTP
  • 2
    Combining stream and historical analytics
  • 1
    OLTP

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Cons of Clickhouse
Cons of Druid
  • 5
    Slow insert operations
  • 3
    Limited sql support
  • 2
    Joins are not supported well
  • 1
    Complexity

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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.

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 Clickhouse?
What companies use Druid?
See which teams inside your own company are using Clickhouse or Druid.
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What tools integrate with Clickhouse?
What tools integrate with Druid?

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Blog Posts

Dec 22 2021 at 5:41AM

Pinterest

MySQLKafkaDruid+3
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What are some alternatives to Clickhouse and Druid?
Cassandra
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.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
InfluxDB
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
See all alternatives