DBMS > Alibaba Cloud Table Store vs. eXtremeDB vs. Microsoft SQL Server vs. Newts vs. SAP SQL Anywhere

System Properties Comparison Alibaba Cloud Table Store vs. eXtremeDB vs. Microsoft SQL Server vs. Newts vs. SAP SQL Anywhere

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Wide column store

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.mcobject.com

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

opennms.github.io/newts

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.mcobject.com/docs/extremedb.htm

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

github.com/OpenNMS/newts/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Alibaba

McObject

Microsoft

OpenNMS Group

SAP

formerly Sybase

Initial release

2016

2001

1989

2014

1992

Current release

8.2, 2021

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

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 and C++

C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

HTTP REST
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
Python

.Net
C
C#
C++
Java
Lua
Python
Scala

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

Java

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

Server-side scripts

Stored procedures

yes

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

yes, in C/C++, Java, .Net or Perl

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning / sharding

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

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes, but depending on the SQL-Server Edition

selectable replication factor

based on Cassandra

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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