DBMS > AllegroGraph vs. Oracle Berkeley DB vs. RDFox vs. Snowflake vs. WakandaDB

System Properties Comparison AllegroGraph vs. Oracle Berkeley DB vs. RDFox vs. Snowflake vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

High performance knowledge graph and semantic reasoning engine

Cloud-based data warehousing service for structured and semi-structured data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
RDF store

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

Relational 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
	#8	Vector DBMS

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

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

allegrograph.com

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

www.oxfordsemantic.tech

www.snowflake.com

wakanda.github.io

Technical documentation

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

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

docs.oxfordsemantic.tech

docs.snowflake.net/manuals/index.html

wakanda.github.io/doc

Developer

Franz Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oxford Semantic Technologies

Snowflake Computing Inc.

Wakanda SAS

Initial release

2004

1994

2017

2014

2012

Current release

8.0, December 2023

18.1.40, May 2020

6.0, Septermber 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

commercial license available

commercial

Open Source

AGPLv3, extended commercial license available

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

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

C++

C++, JavaScript

Server operating systems

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

RDF schemas

schema-free

yes

RDF schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API
SPARQL 1.1

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.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
Java

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

yes

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

replication via a shared file system

yes

none

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Roles, resources, and access types

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

yes

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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