DBMS > Kyligence Enterprise vs. Microsoft SQL Server vs. OpenQM vs. PostgreSQL vs. SiteWhere

System Properties Comparison Kyligence Enterprise vs. Microsoft SQL Server vs. OpenQM vs. PostgreSQL vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

kyligence.io/kyligence-enterprise

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.postgresql.org

github.com/sitewhere/sitewhere

Technical documentation

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

www.postgresql.org/docs

sitewhere1.sitewhere.io/index.html

Developer

Kyligence, Inc.

Microsoft

Rocket Software, originally Martin Phillips

PostgreSQL Global Development Group

www.postgresql.org/developer

SiteWhere

Initial release

2016

1989

1993

1989

1989: Postgres, 1996: PostgreSQL

2010

Current release

SQL Server 2022, November 2022

3.4-12

16.3, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

Server operating systems

Linux

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

with some exceptions

yes

predefined scheme

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

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

HTTP REST

Supported programming languages

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

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

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

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

based on HBase

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

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

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