DBMS > Apache Kylin vs. Greenplum vs. H2 vs. Ingres vs. Microsoft SQL Server

System Properties Comparison Apache Kylin vs. Greenplum vs. H2 vs. Ingres vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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.

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

Well established RDBMS

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

kylin.apache.org

greenplum.org

www.h2database.com

www.actian.com/databases/ingres

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

Technical documentation

kylin.apache.org/docs

docs.greenplum.org

www.h2database.com/html/main.html

docs.actian.com/ingres

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

Developer

Apache Software Foundation, originally contributed from eBay Inc

Pivotal Software Inc.

Thomas Mueller

Actian Corporation

Microsoft

Initial release

2015

2005

1974

originally developed at University Berkely in early 1970s

1989

Current release

3.1.0, July 2020

7.0.0, September 2023

2.2.220, July 2023

11.2, May 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

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

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

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

since Version 4.2

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

Supported programming languages

C
Java
Perl
Python
R

Java

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

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

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Ingres Replicator

yes, but depending on the SQL-Server Edition

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

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

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