DBMS > 4D vs. Apache Phoenix vs. KairosDB vs. Microsoft Azure Cosmos DB vs. RDFox

System Properties Comparison 4D vs. Apache Phoenix vs. KairosDB vs. Microsoft Azure Cosmos DB vs. RDFox

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A scale-out RDBMS with evolutionary schema built on Apache HBase

Distributed Time Series DBMS based on Cassandra or H2

Globally distributed, horizontally scalable, multi-model database service

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

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

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

www.4d.com

phoenix.apache.org

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

www.oxfordsemantic.tech

Technical documentation

developer.4d.com

phoenix.apache.org

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

docs.oxfordsemantic.tech

Developer

4D, Inc

Apache Software Foundation

Microsoft

Oxford Semantic Technologies

Initial release

1984

2014

2013

2014

2017

Current release

v20, April 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.2.2, November 2018

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

C++

Server operating systems

OS X
Windows

Linux
Unix
Windows

Linux
OS X
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

RDF schemas

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

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC

Graphite protocol
HTTP REST
Telnet API

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

RESTful HTTP API
SPARQL 1.1

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Java
JavaScript

Node.js
PHP
Python

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

C
Java

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

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

User concepts

Access control

Users and groups

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

simple password-based access control

Access rights can be defined down to the item level

Roles, resources, and access types

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.