DBMS > AgensGraph vs. Microsoft SQL Server vs. Netezza vs. Postgres-XL

System Properties Comparison AgensGraph vs. Microsoft SQL Server vs. Netezza vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

bitnine.net/agensgraph

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

www.ibm.com/products/netezza

www.postgres-xl.org

Technical documentation

bitnine.net/documentation

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

www.postgres-xl.org/documentation

Developer

Bitnine Global Inc.

Microsoft

IBM

Initial release

2016

1989

2000

2014

since 2012, originally named StormDB

Current release

2.1, December 2018

SQL Server 2022, November 2022

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

restricted free version is available

commercial

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux

included in appliance

Linux
macOS

Data scheme

depending on used data model

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

Cypher Query Language
JDBC

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

JDBC
ODBC
OLE DB

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

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

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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