DBMS > AnzoGraph DB vs. JaguarDB vs. Microsoft Azure AI Search vs. Netezza vs. Oracle

System Properties Comparison AnzoGraph DB vs. JaguarDB vs. Microsoft Azure AI Search vs. Netezza vs. Oracle

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

Performant, highly scalable DBMS for AI and IoT applications

Search-as-a-service for web and mobile app development

Data warehouse and analytics appliance part of IBM PureSystems

Widely used RDBMS

Primary database model

Graph DBMS
RDF store

Key-value store
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

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

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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.jaguardb.com

azure.microsoft.com/en-us/services/search

www.ibm.com/products/netezza

www.oracle.com/database

Technical documentation

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

www.jaguardb.com/support.html

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

Developer

Cambridge Semantics

DataJaguar, Inc.

Microsoft

IBM

Oracle

Initial release

2018

2015

2000

1980

Current release

2.3, January 2021

3.3 July 2023

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPL V3.0

commercial

restricted free version is 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++

the server part. Clients available in other languages

C and C++

Server operating systems

Linux

hosted

Linux

included in appliance

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

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

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.

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

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
ODBC

RESTful HTTP API

JDBC
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Python

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

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

Implicit feature of the cloud service

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication
Source-replica replication

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

Eventual Consistency

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 level can be parameterized

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'

User concepts

Access control

Access rights for users and roles

rights management via user accounts

yes

using Azure authentication

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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