DBMS > HugeGraph vs. Oracle Coherence vs. OrientDB vs. STSdb

System Properties Comparison HugeGraph vs. Oracle Coherence vs. OrientDB vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Oracles in-memory data grid solution

Multi-model DBMS (Document, Graph, Key/Value)

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Graph DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Key-value store

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/java/coherence

orientdb.org

github.com/STSSoft/STSdb4

Technical documentation

hugegraph.apache.org/docs

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

www.orientdb.com/docs/last/index.html

Developer

Baidu

Oracle

OrientDB LTD; CallidusCloud; SAP

STS Soft SC

Initial release

2018

2007

2010

2011

Current release

0.9

14.1, August 2023

3.2.29, March 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2

Open Source

GPLv2, commercial license 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

Server operating systems

Linux
macOS
Unix

All OS with a Java VM

All OS with a Java JDK (>= JDK 6)

Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like query language, no joins

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JCache
JPA
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.NET Client API

Supported programming languages

Groovy
Java
Python

.Net
C++
Java

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java, Javascript

Triggers

yes

Live Events

Hooks

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes, with selectable consistency level

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

relationship in graphs

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Users, roles and permissions

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

Microservices with Major New Coherence and Helidon Releases
9 August 2022, blogs.oracle.com

New solutions for Oracle WebLogic on Azure Virtual Machines
1 April 2021, Microsoft

Nike achieves scalability and performance with Oracle Coherence & Exadata
20 December 2012, blogs.oracle.com

Hazelcast takes on proprietary Oracle in the In-Memory arena
17 June 2014, DatacenterDynamics

GridGain: Product Overview and Analysis
5 June 2019, eWeek

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The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

OrientDB: A Flexible and Scalable Multi-Model NoSQL DBMS
21 January 2022, Open Source For You

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

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14 March 2019, VentureBeat

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11 May 2021, TechTarget

provided by Google News

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