DBMS > DataFS vs. MarkLogic vs. Microsoft Azure Cosmos DB vs. YottaDB

System Properties Comparison DataFS vs. MarkLogic vs. Microsoft Azure Cosmos DB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Operational and transactional Enterprise NoSQL database

Globally distributed, horizontally scalable, multi-model database service

A fast and solid embedded Key-value store

Primary database model

Object oriented DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Graph DBMS

Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

newdatabase.com

www.progress.com/marklogic

azure.microsoft.com/services/cosmos-db

yottadb.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.progress.com/marklogic/documentation

learn.microsoft.com/azure/cosmos-db

yottadb.com/resources/documentation

Developer

Mobiland AG

MarkLogic Corp.

Microsoft

YottaDB, LLC

Initial release

2018

2001

2014

2001

Current release

1.1.263, October 2022

11.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

AGPL 3.0

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

C++

Server operating systems

Windows

Linux
OS X
Windows

hosted

Docker
Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

SQL

Support of SQL

yes

SQL92

SQL-like query language

by using the Octo plugin

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.Net
C
C#
C++
VB.Net

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

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

JavaScript

Triggers

no, except callback-events from server when changes happened

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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

User concepts

Access control

Windows-Profile

Role-based access control at the document and subdocument levels

Access rights can be defined down to the item level

Users and groups based on OS-security mechanisms

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