DBMS > AllegroGraph vs. DataFS vs. EsgynDB vs. Oracle Berkeley DB vs. RocksDB

System Properties Comparison AllegroGraph vs. DataFS vs. EsgynDB vs. Oracle Berkeley DB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Widely used in-process key-value store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Object oriented DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Spatial DBMS

Graph DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

allegrograph.com

newdatabase.com

www.esgyn.cn

www.oracle.com/database/technologies/related/berkeleydb.html

rocksdb.org

Technical documentation

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

dev.mobiland.com/Overview.xsp

docs.oracle.com/cd/E17076_05/html/index.html

github.com/facebook/rocksdb/wiki

Developer

Franz Inc.

Mobiland AG

Esgyn

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Facebook, Inc.

Initial release

2004

2018

2015

1994

2013

Current release

8.0, December 2023

1.1.263, October 2022

18.1.40, May 2020

9.2.1, May 2024

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

commercial license available

Open Source

BSD

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

C++, Java

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

Linux
OS X
Windows

Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

yes

RDF schemas

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

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

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API
SPARQL

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Java Stored Procedures

Triggers

yes

no, except callback-events from server when changes happened

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

with Federation

Proprietary Sharding system

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Windows-Profile

fine grained access rights according to SQL-standard

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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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

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