DBMS > IBM Db2 warehouse vs. MarkLogic vs. Microsoft SQL Server vs. RethinkDB vs. SwayDB

System Properties Comparison IBM Db2 warehouse vs. MarkLogic vs. Microsoft SQL Server vs. RethinkDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Document store

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

www.ibm.com/products/db2/warehouse

www.progress.com/marklogic

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

rethinkdb.com

swaydb.simer.au

Technical documentation

www.progress.com/marklogic/documentation

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

rethinkdb.com/docs

Developer

IBM

MarkLogic Corp.

Microsoft

The Linux Foundation

since July 2017

Simer Plaha

Initial release

2014

2001

1989

2009

2018

Current release

11.0, December 2022

SQL Server 2022, November 2022

2.4.1, August 2020

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache Version 2

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

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)

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Kotlin
Scala

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes

via XQuery or JavaScript

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

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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

ACID

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

yes, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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