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

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

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

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.jaguardb.com

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

www.microsoft.com/en-us/sql-server

www.ibm.com/products/netezza

Technical documentation

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

www.jaguardb.com/support.html

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

learn.microsoft.com/en-US/sql/sql-server

Developer

Cambridge Semantics

DataJaguar, Inc.

Microsoft

IBM

Initial release

2018

2015

1989

2000

Current release

2.3, January 2021

3.3 July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPL V3.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

hosted

Linux
Windows

Linux

included in appliance

Data scheme

Schema-free and OWL/RDFS-schema support

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.

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
Python

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

C#
Java
JavaScript
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions and aggregates

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

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

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

Access rights for users and roles

rights management via user accounts

yes

using Azure authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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