DBMS > GBase vs. HugeGraph vs. Oracle vs. SQL.JS vs. Vitess

System Properties Comparison GBase vs. HugeGraph vs. Oracle vs. SQL.JS vs. Vitess

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

Widely used RDBMS

Port of SQLite to JavaScript

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/database

sql.js.org

vitess.io

Technical documentation

hugegraph.apache.org/docs

docs.oracle.com/en/database

sql.js.org/documentation/index.html

vitess.io/docs

Developer

General Data Technology Co., Ltd.

Baidu

Oracle

Alon Zakai

enhancements implemented by others

The Linux Foundation, PlanetScale

Initial release

2004

2018

1980

2012

2013

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

23c, September 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0, commercial licenses 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 and C++

JavaScript

Server operating systems

Linux

Linux
macOS
Unix

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

Docker
Linux
macOS

Data scheme

yes

Schemaless in JSON and XML columns

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

with proprietary extensions

yes

SQL-92 is not fully supported

yes

with proprietary extensions

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)

JavaScript API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Groovy
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

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

asynchronous Gremlin script jobs

PL/SQL

also stored procedures in Java possible

yes

proprietary syntax

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

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

yes

Users, roles and permissions

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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