DBMS > GBase vs. HugeGraph vs. OceanBase vs. Sadas Engine

System Properties Comparison GBase vs. HugeGraph vs. OceanBase vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

A distributed, high available RDBMS compatible with Oracle and MySQL

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

en.oceanbase.com

www.sadasengine.com

Technical documentation

hugegraph.apache.org/docs

en.oceanbase.com/docs/oceanbase-database

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

General Data Technology Co., Ltd.

Baidu

OceanBase

previously Alibaba and Ant Group

SADAS s.r.l.

Initial release

2004

2018

2010

2006

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

4.3.0, April 2024

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Commercial license available

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, Java, Python

Java

C++

Server operating systems

Linux

Linux
macOS
Unix

Linux

AIX
Linux
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

also supports composite index and range index

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Groovy
Java
Python

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

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

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication using Paxos

none

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

Transaction concepts

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

ACID

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

managed by 'Learn by Usage'

User concepts

Access control

yes

Users, roles and permissions

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

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