DBMS > ArcadeDB vs. eXtremeDB vs. HugeGraph vs. Oracle

System Properties Comparison ArcadeDB vs. eXtremeDB vs. HugeGraph vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Natively in-memory DBMS with options for persistency, high-availability and clustering

A fast-speed and highly-scalable Graph DBMS

Widely used RDBMS

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS
Time Series 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

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

arcadedb.com

www.mcobject.com

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/database

Technical documentation

docs.arcadedb.com

www.mcobject.com/docs/extremedb.htm

hugegraph.apache.org/docs

docs.oracle.com/en/database

Developer

Arcade Data

McObject

Baidu

Oracle

Initial release

2021

2001

2018

1980

Current release

September 2021

8.2, 2021

0.9

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is 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 and C++

Java

C and C++

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS
Unix

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

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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.

support of XML interfaces available

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

with the option: eXtremeSQL

yes

with proprietary extensions

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

.Net
C
C#
C++
Java
Lua
Python
Scala

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

PL/SQL

also stored procedures in Java possible

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

yes

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

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

edges in graph

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

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

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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