DBMS > Alibaba Cloud Table Store vs. MarkLogic vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

System Properties Comparison Alibaba Cloud Table Store vs. MarkLogic vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Wide column store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Document store

Multivalue DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

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	7.18
Rank	#52	Overall
	#8	Document stores

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

www.alibabacloud.com/product/table-store

www.progress.com/marklogic

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

realm.io

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

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.progress.com/marklogic/documentation

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

realm.io/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Alibaba

MarkLogic Corp.

Microsoft

Realm, acquired by MongoDB in May 2019

Rocket Software

Initial release

2016

2001

1989

2014

1985

Current release

11.0, December 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

SQL92

yes

APIs and other access methods

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)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Java
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
Java

with Android only
Objective-C
React Native
Swift

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

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

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

yes, but depending on the SQL-Server Edition

none

Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

ACID

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

ACID

configurable

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, with Range Indexes

yes

In-Memory realm

User concepts

Access control

Access rights based on subaccounts and tokens

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

yes

Access rights according to SQL-standard and operating system based

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