DBMS > AllegroGraph vs. FatDB vs. HarperDB vs. RDF4J

System Properties Comparison AllegroGraph vs. FatDB vs. HarperDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Key-value store

Document store

RDF store

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

allegrograph.com

www.harperdb.io

rdf4j.org

Technical documentation

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

docs.harperdb.io/docs

rdf4j.org/documentation

Developer

Franz Inc.

FatCloud

HarperDB

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

Initial release

2004

2012

2017

2004

Current release

8.0, December 2023

3.1, August 2021

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free community edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Node.js

Java

Server operating systems

Linux
OS X
Windows

Windows

Linux
OS X

Linux
OS X
Unix
Windows

Data scheme

yes

RDF schemas

schema-free

dynamic schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL

Support of SQL

SPARQL is used as query language

Via inetgration in SQL Server

SQL-like data manipulation statements

APIs and other access methods

RESTful HTTP API
SPARQL

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

via applications

Custom Functions

since release 3.1

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

in-memory storage is supported as well

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

Can implement custom security layer via applications

Access rights for users and roles

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

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