DBMS > AnzoGraph DB vs. Axibase vs. Netezza vs. Oracle vs. RDFox

System Properties Comparison AnzoGraph DB vs. Axibase vs. Netezza vs. Oracle vs. RDFox

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Data warehouse and analytics appliance part of IBM PureSystems

Widely used RDBMS

High performance knowledge graph and semantic reasoning engine

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

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

Website

cambridgesemantics.com/anzograph

axibase.com/docs/atsd/finance

www.ibm.com/products/netezza

www.oracle.com/database

www.oxfordsemantic.tech

Technical documentation

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

docs.oracle.com/en/database

docs.oxfordsemantic.tech

Developer

Cambridge Semantics

Axibase Corporation

IBM

Oracle

Oxford Semantic Technologies

Initial release

2018

2013

2000

1980

2017

Current release

2.3, January 2021

15585

23c, September 2023

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux

included in appliance

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

yes

RDF schemas

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

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

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API
SPARQL 1.1

Supported programming languages

C++
Java
Python

Go
Java
PHP
Python
R
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Multi-source replication
Source-replica replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

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

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Roles, resources, and access types

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