DBMS > Apache Phoenix vs. EsgynDB vs. Heroic vs. TerarkDB vs. VoltDB

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Heroic vs. TerarkDB vs. VoltDB

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

phoenix.apache.org

www.esgyn.cn

github.com/spotify/heroic

github.com/bytedance/terarkdb

www.voltdb.com

Technical documentation

phoenix.apache.org

spotify.github.io/heroic

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.voltdb.com

Developer

Apache Software Foundation

Esgyn

Spotify

ByteDance, originally Terark

VoltDB Inc.

Initial release

2014

2015

2014

2016

2010

Current release

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

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

restricted open source version available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

C++

Java, C++

Server operating systems

Linux
Unix
Windows

Linux

Linux
OS X

for development

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Java

Triggers

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

yes

none

Multi-source replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

show all

Recent citations in the news

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

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

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

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27 March 2017, SDTimes.com

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