DBMS > Greenplum vs. H2GIS vs. Microsoft SQL Server vs. openGemini

System Properties Comparison Greenplum vs. H2GIS vs. Microsoft SQL Server vs. openGemini

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Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Spatial extension of H2

Microsofts flagship relational DBMS

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Website

greenplum.org

www.h2gis.org

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

www.opengemini.org
github.com/openGemini

Technical documentation

docs.greenplum.org

www.h2gis.org/docs/home

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

docs.opengemini.org/guide

Developer

Pivotal Software Inc.

CNRS

Microsoft

Huawei and openGemini community

Initial release

2005

2013

1989

2022

Current release

7.0.0, September 2023

SQL Server 2022, November 2022

1.1, July 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

Linux

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

HTTP REST

Supported programming languages

C
Java
Perl
Python
R

Java

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

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

based on H2

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

based on H2

yes, but depending on the SQL-Server Edition

yes

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

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

fine grained access rights according to SQL-standard

yes

based on H2

fine grained access rights according to SQL-standard

Administrators and common users accounts

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