DBMS > Alibaba Cloud Table Store vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. OushuDB vs. Transbase

System Properties Comparison Alibaba Cloud Table Store vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. OushuDB vs. Transbase

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

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Wide column store

Event Store
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	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.ibm.com/products/db2-event-store

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

www.oushu.com/product/oushuDB

www.transaction.de/en/products/transbase.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.ibm.com/docs/en/db2-event-store

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

www.oushu.com/documentation

www.transaction.de/en/products/transbase/features.html

Developer

Alibaba

IBM

Microsoft

Oushu

Transaction Software GmbH

Initial release

2016

2017

1989

1987

Current release

2.0

SQL Server 2022, November 2022

4.0.1, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

C and C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python

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

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

C
C++

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

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

yes

Triggers

yes

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Active-active shard replication

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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