DBMS > AllegroGraph vs. Amazon SimpleDB vs. RDF4J vs. VoltDB

System Properties Comparison AllegroGraph vs. Amazon SimpleDB vs. RDF4J vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

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

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store

RDF store

Relational 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	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

allegrograph.com

aws.amazon.com/simpledb

rdf4j.org

www.voltdb.com

Technical documentation

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

docs.aws.amazon.com/simpledb

rdf4j.org/documentation

docs.voltdb.com

Developer

Franz Inc.

Amazon

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

VoltDB Inc.

Initial release

2004

2007

2004

2010

Current release

8.0, December 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

Linux
OS X

for development

Data scheme

yes

RDF schemas

schema-free

yes

RDF Schemas

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.

bulk load of XML files possible

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

SPARQL is used as query language

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding must be implemented in the application

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be specified for read operations

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

ACID

Isolation support depends on the API used

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

in-memory storage is supported as well

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

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users and roles with access to stored procedures

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

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17 April 2024

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3 April 2024

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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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More resources

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