DBMS > Apache Phoenix vs. DataFS vs. EsgynDB vs. Realm vs. STSdb

System Properties Comparison Apache Phoenix vs. DataFS vs. EsgynDB vs. Realm vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Graph DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

phoenix.apache.org

dev.mobiland.com/Overview.xsp

realm.io/docs

Developer

Apache Software Foundation

Mobiland AG

Esgyn

Realm, acquired by MongoDB in May 2019

STS Soft SC

Initial release

2014

2018

2015

2014

2011

Current release

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

1.1.263, October 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

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

C++, Java

Server operating systems

Linux
Unix
Windows

Windows

Linux

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

.NET Client API

Supported programming languages

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

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Triggers

no, except callback-events from server when changes happened

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

In-Memory realm

User concepts

Access control

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

Windows-Profile

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

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11 August 2021, Krishna Maheshwari (sponsor)

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

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27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps | Amazon Web Services
2 June 2016, AWS Blog

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9 June 2020, diginomica

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12 September 2017, Solutions Review

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31 May 2016, EU-Startups

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

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27 February 2021, DataDrivenInvestor

provided by Google News

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