DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Doris vs. Firebase Realtime Database vs. MySQL vs. Splice Machine

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Doris vs. Firebase Realtime Database vs. MySQL vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

An MPP-based analytics DBMS embracing the MySQL protocol

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Widely used open source RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

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

firebase.google.com/products/realtime-database

www.mysql.com

splicemachine.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

github.com/apache/doris/wiki

firebase.google.com/docs/database

dev.mysql.com/doc

splicemachine.com/how-it-works

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation, originally contributed from Baidu

Google

acquired by Google 2014

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

Initial release

2016

2017

2012

1995

2014

Current release

1.2.2, February 2023

8.4.0, April 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
Java
Perl
Python
R

Java

Java
JavaScript
Objective-C

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

limited functionality with using 'rules'

yes

proprietary syntax

yes

Java

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

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

yes, based on authentication and database rules

Users with fine-grained authorization concept

no user groups or roles

Access rights for users, groups and roles according to SQL-standard

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