DBMS > AnzoGraph DB vs. RDF4J vs. SAP SQL Anywhere

System Properties Comparison AnzoGraph DB vs. RDF4J vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Graph DBMS
RDF store

RDF store

Relational DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Website

cambridgesemantics.com/anzograph

rdf4j.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

rdf4j.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Cambridge Semantics

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

SAP

formerly Sybase

Initial release

2018

2004

1992

Current release

2.3, January 2021

17, July 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C++
Java
Python

Java
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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15 April 2019, InfoWorld

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8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
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Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
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