DBMS > HugeGraph vs. OpenMLDB vs. Oracle Coherence vs. RDF4J

System Properties Comparison HugeGraph vs. OpenMLDB vs. Oracle Coherence vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

An open-source machine learning database that provides a feature platform for training and inference

Oracles in-memory data grid solution

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/hugegraph
hugegraph.apache.org

openmldb.ai

www.oracle.com/java/coherence

rdf4j.org

Technical documentation

hugegraph.apache.org/docs

openmldb.ai/docs/zh/main

docs.oracle.com/en/middleware/standalone/coherence

rdf4j.org/documentation

Developer

Baidu

4 Paradigm Inc.

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2018

2020

2007

2004

Current release

0.9

2024-2 February 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

C++, Java, Scala

Java

Server operating systems

Linux
macOS
Unix

Linux

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

Fixed schema

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
SQLAlchemy

JCache
JPA
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Groovy
Java
Python

C++
Go
Java
Python
Scala

.Net
C++
Java

Java
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

configurable

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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