DBMS > JanusGraph vs. Teradata Aster vs. Trafodion vs. Virtuoso

System Properties Comparison JanusGraph vs. Teradata Aster vs. Trafodion vs. Virtuoso

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A Graph DBMS optimized for distributed clusters

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

Platform for big data analytics on multistructured data sources and types

Transactional SQL-on-Hadoop DBMS

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

Graph DBMS

Relational DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Spatial DBMS

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	4.26
Rank	#78	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#42	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

janusgraph.org

trafodion.apache.org

virtuoso.openlinksw.com

Technical documentation

docs.janusgraph.org

trafodion.apache.org/documentation.html

docs.openlinksw.com/virtuoso

Developer

Linux Foundation; originally developed as Titan by Aurelius

Teradata

Apache Software Foundation, originally developed by HP

OpenLink Software

Initial release

2017

2005

2014

1998

Current release

0.6.3, February 2023

2.3.0, February 2019

7.2.11, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended 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

C++, Java

Server operating systems

Linux
OS X
Unix
Windows

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

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.

yes

in Aster File Store

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

Supported programming languages

Clojure
Java
Python

C
C#
C++
Java
Python
R

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

R packages

Java Stored Procedures

yes

Virtuoso PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

yes, via HBase

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

SQL Map-Reduce Framework

yes

via user defined functions and HBase

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

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 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

fine grained access rights according to SQL-standard

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
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Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
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Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more

Key customers

Broad use across enterprises and governments including — European Union (EU) US Government...
» more

Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more

Licensing and pricing models

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

Database Deep Dives: JanusGraph
8 August 2019, IBM

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Simple Deployment of a Graph Database: JanusGraph | by Edward Elson Kosasih
12 October 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News

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23 May 2014, Northwestern Engineering

Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

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22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

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