DBMS > gStore vs. JanusGraph vs. Oracle Coherence vs. Spark SQL

System Properties Comparison gStore vs. JanusGraph vs. Oracle Coherence vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Oracles in-memory data grid solution

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

en.gstore.cn

janusgraph.org

www.oracle.com/java/coherence

spark.apache.org/sql

Technical documentation

en.gstore.cn/#/enDocs

docs.janusgraph.org

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Apache Software Foundation

Initial release

2016

2017

2007

2014

Current release

1.2, November 2023

0.6.3, February 2023

14.1, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

C++

Java

Scala

Server operating systems

Linux

Linux
OS X
Unix
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free and OWL/RDFS-schema support

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API
SPARQL 1.1

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java
Python

.Net
C++
Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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, Role-Based Access Control (RBAC) supported

User authentification and security via Rexster Graph Server

authentification to access the cache via certificates or http basic authentication

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