DBMS > AllegroGraph vs. Ingres vs. JanusGraph vs. SiteWhere vs. SQLite

System Properties Comparison AllegroGraph vs. Ingres vs. JanusGraph vs. SiteWhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Well established RDBMS

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

allegrograph.com

www.actian.com/databases/ingres

janusgraph.org

github.com/sitewhere/sitewhere

www.sqlite.org

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.actian.com/ingres

docs.janusgraph.org

sitewhere1.sitewhere.io/index.html

www.sqlite.org/docs.html

Developer

Franz Inc.

Actian Corporation

Linux Foundation; originally developed as Titan by Aurelius

SiteWhere

Dwayne Richard Hipp

Initial release

2004

1974

originally developed at University Berkely in early 1970s

2017

2010

2000

Current release

8.0, December 2023

11.2, May 2022

0.6.3, February 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Open Source

Public Domain

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

Server operating systems

Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

server-less

Data scheme

yes

RDF schemas

yes

predefined scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

bulk load of XML files possible

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API
SPARQL

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Clojure
Java
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

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

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Ingres Replicator

yes

selectable replication factor

based on HBase

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

MVCC

yes

via file-system locks

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

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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