DBMS > Apache Phoenix vs. MySQL vs. Percona Server for MongoDB vs. RethinkDB vs. Sequoiadb

System Properties Comparison Apache Phoenix vs. MySQL vs. Percona Server for MongoDB vs. RethinkDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

phoenix.apache.org

www.mysql.com

www.percona.com/mongodb/software/percona-server-for-mongodb

rethinkdb.com

www.sequoiadb.com

Technical documentation

phoenix.apache.org

dev.mysql.com/doc

docs.percona.com/percona-distribution-for-mongodb

rethinkdb.com/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Percona

The Linux Foundation

since July 2017

Sequoiadb Ltd.

Initial release

2014

1995

2015

2009

2013

Current release

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

8.4.0, April 2024

3.4.10-2.10, November 2017

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 2

Open Source

Apache Version 2

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

oid, date, timestamp, binary, regex

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

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

JavaScript

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica 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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic single-document operations

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC based

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

via In-Memory Engine

User concepts

Access control

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

yes

users and table-level permissions

simple password-based access control

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