DBMS > AllegroGraph vs. H2 vs. Kyligence Enterprise vs. Microsoft SQL Server vs. Netezza

System Properties Comparison AllegroGraph vs. H2 vs. Kyligence Enterprise vs. Microsoft SQL Server vs. Netezza

Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A distributed analytics engine for big data, built on top of Apache Kylin

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial 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
	#7	Vector DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

allegrograph.com

www.h2database.com

kyligence.io/kyligence-enterprise

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

www.ibm.com/products/netezza

Technical documentation

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

www.h2database.com/html/main.html

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

Developer

Franz Inc.

Thomas Mueller

Kyligence, Inc.

Microsoft

IBM

Initial release

2004

2005

2016

1989

2000

Current release

8.0, December 2023

2.2.220, July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
Windows

Linux

included in appliance

Data scheme

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.

bulk load of XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
OLE DB

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Java

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

yes

JavaScript or Common Lisp

Java Stored Procedures and User-Defined Functions

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

with Federation

none

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
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

News

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9 February 2024

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23 January 2024

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