DBMS > Alibaba Cloud Table Store vs. Datomic vs. IBM Db2 vs. Ingres vs. Microsoft SQL Server

System Properties Comparison Alibaba Cloud Table Store vs. Datomic vs. IBM Db2 vs. Ingres vs. Microsoft SQL Server

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Common in IBM host environments, 2 different versions for host and Windows/Linux

Well established RDBMS

Microsofts flagship relational DBMS

Primary database model

Wide column store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.datomic.com

www.ibm.com/products/db2

www.actian.com/databases/ingres

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

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

www.ibm.com/docs/en/db2

docs.actian.com/ingres

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

Developer

Alibaba

Cognitect

IBM

Actian Corporation

Microsoft

Initial release

2016

2012

1983

host version

1974

originally developed at University Berkely in early 1970s

1989

Current release

1.0.7075, December 2023

12.1, October 2016

11.2, May 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

free version is available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, Clojure

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

Supported programming languages

Java
Python

Clojure
Java

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

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

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

yes

with separate tools (MQ, InfoSphere)

Ingres Replicator

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

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