DBMS > Kinetica vs. MarkLogic vs. Microsoft SQL Server vs. NuoDB vs. OpenQM

System Properties Comparison Kinetica vs. MarkLogic vs. Microsoft SQL Server vs. NuoDB vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

www.kinetica.com

www.marklogic.com

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

www.3ds.com/nuodb-distributed-sql-database

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

Technical documentation

docs.kinetica.com

docs.marklogic.com

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

doc.nuodb.com

Developer

Kinetica

MarkLogic Corp.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Rocket Software, originally Martin Phillips

Initial release

2012

2001

1989

2013

1993

Current release

7.1, August 2021

11.0, December 2022

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

commercial

limited edition free

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

Schema can be enforced

yes

with some exceptions

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL92

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

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

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

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

Java, SQL

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

data is dynamically stored/cached on the nodes where it is read/written

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

can act as a resource manager in an XA/JTA transaction

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

yes, with Range Indexes

yes

Temporary table

User concepts

Access control

Access rights for users and roles on table level

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access rights can be defined down to the item level

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