DBMS > 4D vs. Apache Phoenix vs. Faircom DB vs. Firebase Realtime Database vs. KairosDB

System Properties Comparison 4D vs. Apache Phoenix vs. Faircom DB vs. Firebase Realtime Database vs. KairosDB

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Time Series 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	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

www.4d.com

phoenix.apache.org

www.faircom.com/products/faircom-db

firebase.google.com/products/realtime-database

github.com/kairosdb/kairosdb

Technical documentation

developer.4d.com

phoenix.apache.org

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

firebase.google.com/docs/database

kairosdb.github.io

Developer

4D, Inc

Apache Software Foundation

FairCom Corporation

Google

acquired by Google 2014

Initial release

1984

2014

1979

2012

2013

Current release

v20, April 2023

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

V12, November 2020

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Restricted, free version available

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

Java

ANSI C, C++

Java

Server operating systems

OS X
Windows

Linux
Unix
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

Linux
OS X
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL

Support of SQL

yes

close to SQL 92

yes

yes, ANSI SQL with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Android
iOS
JavaScript API
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

4D proprietary IDE
PHP

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java
JavaScript
Objective-C

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

yes, based on authentication and database rules

simple password-based access control

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