DBMS > JanusGraph vs. RDF4J vs. SAP HANA vs. Warp 10

System Properties Comparison JanusGraph vs. RDF4J vs. SAP HANA vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

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

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

In-memory, column based data store. Available as appliance or cloud service

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

janusgraph.org

rdf4j.org

www.sap.com/products/hana.html

www.warp10.io

Technical documentation

docs.janusgraph.org

rdf4j.org/documentation

help.sap.com/hana

www.warp10.io/content/02_Getting_started

Developer

Linux Foundation; originally developed as Titan by Aurelius

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

SAP

SenX

Initial release

2017

2004

2010

2015

Current release

0.6.3, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

schema-free

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

yes

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

Clojure
Java
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

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

in-memory storage is supported as well

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

User authentification and security via Rexster Graph Server

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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