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

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

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

An MPP-based analytics DBMS embracing the MySQL protocol

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

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.60
Rank	#247	Overall
	#113	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

Website

www.4d.com

doris.apache.org
github.com/apache/doris

phoenix.apache.org

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

Technical documentation

developer.4d.com

github.com/apache/doris/wiki

phoenix.apache.org

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

Developer

4D, Inc

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Microsoft

Initial release

1984

2017

2014

2013

2014

Current release

v20, April 2023

1.2.2, February 2023

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

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

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Implementation language

Java

Server operating systems

OS X
Windows

Linux

Linux
Unix
Windows

Linux
OS X
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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

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
MySQL client

JDBC

Graphite protocol
HTTP REST
Telnet API

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

Supported programming languages

4D proprietary IDE
PHP

Java

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

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

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

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

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

fine grained access rights according to SQL-standard

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

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