DBMS > JanusGraph vs. SiteWhere vs. TerminusDB vs. TigerGraph vs. VoltDB

System Properties Comparison JanusGraph vs. SiteWhere vs. TerminusDB vs. TigerGraph vs. VoltDB

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

M2M integration platform for persisting/querying time series data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
RDF store

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

janusgraph.org

github.com/sitewhere/sitewhere

terminusdb.com

www.tigergraph.com

www.voltdb.com

Technical documentation

docs.janusgraph.org

sitewhere1.sitewhere.io/index.html

terminusdb.github.io/terminusdb/#

docs.tigergraph.com

docs.voltdb.com

Developer

Linux Foundation; originally developed as Titan by Aurelius

SiteWhere

DataChemist Ltd.

VoltDB Inc.

Initial release

2017

2010

2018

2017

2010

Current release

0.6.3, February 2023

11.0.0, January 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL V3

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Prolog, Rust

C++

Java, C++

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Linux

Linux
OS X

for development

Data scheme

yes

predefined scheme

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 query language (WOQL)

SQL-like query language (GSQL)

yes

only a subset of SQL 99

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java
Python

JavaScript
Python

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

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

based on HBase

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

in-memory journaling

yes

Snapshots and command logging

In-memory capabilities

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

User concepts

Access control

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

Role-based access control

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

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

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
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Compose for JanusGraph arrives on Bluemix
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Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

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7 April 2022, SiliconRepublic.com

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TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

TigerGraph partners with Pascal as master distributor for APJ region
10 January 2024, VnExpress International

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Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News

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