DBMS > Apache Phoenix vs. Faircom DB vs. Postgres-XL vs. Realm vs. Transbase

System Properties Comparison Apache Phoenix vs. Faircom DB vs. Postgres-XL vs. Realm vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

phoenix.apache.org

www.faircom.com/products/faircom-db

www.postgres-xl.org

realm.io

www.transaction.de/en/products/transbase.html

Technical documentation

phoenix.apache.org

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

www.postgres-xl.org/documentation

realm.io/docs

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

FairCom Corporation

Realm, acquired by MongoDB in May 2019

Transaction Software GmbH

Initial release

2014

1979

2014

since 2012, originally named StormDB

2014

1987

Current release

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

V12, November 2020

10 R1, October 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Mozilla public license

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

ANSI C, C++

C and C++

Server operating systems

Linux
Unix
Windows

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

easily portable to other OSs

Linux
macOS

Android
Backend: server-less
iOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

yes, ANSI SQL with proprietary extensions

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

user defined functions

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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).

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

Immediate Consistency

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

ACID

MVCC

ACID

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

In-Memory realm

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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