DBMS > Apache Phoenix vs. Cubrid vs. MySQL vs. SAP HANA vs. Vitess

System Properties Comparison Apache Phoenix vs. Cubrid vs. MySQL vs. SAP HANA vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Widely used open source RDBMS

In-memory, column based data store. Available as appliance or cloud service

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

phoenix.apache.org

cubrid.com (korean)
cubrid.org (english)

www.mysql.com

www.sap.com/products/hana.html

vitess.io

Technical documentation

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Oracle

since 2010, originally MySQL AB, then Sun

SAP

The Linux Foundation, PlanetScale

Initial release

2014

2008

1995

2010

2013

Current release

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

11.0, January 2021

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Implementation language

Java

C, C++, Java

C and C++

Server operating systems

Linux
Unix
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Docker
Linux
macOS

Data scheme

yes

late-bound, schema-on-read capabilities

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

proprietary syntax

SQLScript, R

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

yes

Multi-source replication
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

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

table locks or row locks depending on storage engine

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

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 with fine-grained authorization concept

no user groups or roles

yes

Users with fine-grained authorization concept

no user groups or roles

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