DBMS > ClickHouse vs. H2GIS vs. Spark SQL vs. TDSQL for MySQL

System Properties Comparison ClickHouse vs. H2GIS vs. Spark SQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Spatial extension of H2

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Relational DBMS

Document store
Spatial DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

clickhouse.com

www.h2gis.org

spark.apache.org/sql

www.tencentcloud.com/products/dcdb

Technical documentation

clickhouse.com/docs

www.h2gis.org/docs/home

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

www.tencentcloud.com/document/product/1042

Developer

Clickhouse Inc.

CNRS

Apache Software Foundation

Tencent

Initial release

2016

2013

2014

2013

Current release

v24.4.1.2088-stable, May 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

Java

Scala

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC

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
Rust
Scala

3rd party library

Java

Java
Python
R
Scala

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

yes, utilizing Spark Core

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

based on H2

none

Multi-source replication
Source-replica replication

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

yes

based on H2

Users with fine-grained authorization concept

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