DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. GBase vs. HugeGraph vs. MySQL vs. Postgres-XL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. GBase vs. HugeGraph vs. MySQL vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A fast-speed and highly-scalable Graph DBMS

Widely used open source RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Graph DBMS

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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

www.mysql.com

www.postgres-xl.org

Technical documentation

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

hugegraph.apache.org/docs

dev.mysql.com/doc

www.postgres-xl.org/documentation

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

General Data Technology Co., Ltd.

Baidu

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2004

2018

1995

2014

since 2012, originally named StormDB

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

8.4.0, April 2024

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, Java, Python

Java

C and C++

Server operating systems

hosted

Linux

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

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

XML type, but no XML query functionality

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
Java
Perl
Python
R

Groovy
Java
Python

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

asynchronous Gremlin script jobs

yes

proprietary syntax

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

yes

Users, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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