DBMS > Apache Phoenix vs. EsgynDB vs. Realm vs. Transwarp Hippo

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Realm vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

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

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Document store

Vector DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

phoenix.apache.org

www.esgyn.cn

realm.io

www.transwarp.cn/en/subproduct/hippo

Technical documentation

phoenix.apache.org

realm.io/docs

Developer

Apache Software Foundation

Esgyn

Realm, acquired by MongoDB in May 2019

Initial release

2014

2015

2014

2023

Current release

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

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial

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

C++

Server operating systems

Linux
Unix
Windows

Linux

Android
Backend: server-less
iOS
Windows

Linux
macOS

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

yes

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

yes

Role based access control and fine grained access rights

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Recent citations in the news

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2 June 2016, AWS Blog

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25 September 2018, Microsoft

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28 June 2016, ADT Magazine

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28 March 2022, iProgrammer

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