DBMS > IBM Cloudant vs. Linter vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Tibero

System Properties Comparison IBM Cloudant vs. Linter vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

RDBMS for high security requirements

Globally distributed, horizontally scalable, multi-model database service

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

www.ibm.com/products/cloudant

linter.ru

azure.microsoft.com/services/cosmos-db

www.sadasengine.com

us.tmaxsoft.com/products/tibero

Technical documentation

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

relex.ru

Microsoft

SADAS s.r.l.

TmaxSoft

Initial release

2010

1990

2014

2006

2003

Current release

8.0

6, April 2015

License

Commercial or Open Source

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C and C++

C++

C and Assembler

Server operating systems

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

managed by 'Learn by Usage'

planned for next version

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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