DBMS > ClickHouse vs. Spark SQL vs. STSdb

System Properties Comparison ClickHouse vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	12.71
Rank	#46	Overall
	#30	Relational DBMS

Score	23.04
Rank	#35	Overall
	#21	Relational DBMS

Score	0.00
Rank	#356	Overall
	#57	Key-value stores

Website

clickhouse.tech

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

clickhouse.tech/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Clickhouse Inc.

Apache Software Foundation

STS Soft SC

Initial release

2016

2014

2011

Current release

v22.4.5.9-stable, May 2022

3.3.0, June 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

SQL

Support of SQL

Close to ANSI SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

JDBC
ODBC

.NET Client API

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Scala

3rd party library

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

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