DBMS > Microsoft Azure Cosmos DB vs. RDFox vs. RRDtool vs. TimesTen vs. TinkerGraph

System Properties Comparison Microsoft Azure Cosmos DB vs. RDFox vs. RRDtool vs. TimesTen vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

High performance knowledge graph and semantic reasoning engine

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

In-Memory RDBMS compatible to Oracle

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

Relational DBMS

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

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

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

www.oxfordsemantic.tech

oss.oetiker.ch/rrdtool

www.oracle.com/database/technologies/related/timesten.html

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oxfordsemantic.tech

oss.oetiker.ch/rrdtool/doc

docs.oracle.com/database/timesten-18.1

Developer

Microsoft

Oxford Semantic Technologies

Tobias Oetiker

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2017

1999

1998

2009

Current release

6.0, Septermber 2022

1.8.0, 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

commercial

Open Source

Apache 2.0

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++

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

hosted

Linux
macOS
Windows

HP-UX
Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

RDF schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

RESTful HTTP API
SPARQL 1.1

in-process shared library
Pipes

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

TinkerPop 3

Supported programming languages

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

C
Java

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C
C++
Java
PL/SQL

Groovy
Java

Server-side scripts

Stored procedures

JavaScript

PL/SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

replication via a shared file system

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

none

Immediate Consistency or Eventual Consistency depending on configuration

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

optional

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 can be defined down to the item level

Roles, resources, and access types

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.