DBMS > Apache Doris vs. Apache Impala vs. H2GIS vs. MySQL

System Properties Comparison Apache Doris vs. Apache Impala vs. H2GIS vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Analytic DBMS for Hadoop

Spatial extension of H2

Widely used open source RDBMS

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store

Relational DBMS

Document store
Spatial DBMS

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Trend Chart

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

impala.apache.org

www.h2gis.org

www.mysql.com

Technical documentation

github.com/apache/doris/wiki

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

dev.mysql.com/doc

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2013

1995

Current release

1.2.2, February 2023

4.1.0, June 2022

9.0.0, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

LGPL 3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

All languages supporting JDBC/ODBC

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

based on H2

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

based on H2

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

Users with fine-grained authorization concept

no user groups or roles

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