DBMS > Apache Phoenix vs. Microsoft Azure SQL Database vs. Oracle vs. Oracle Coherence vs. Vitess

System Properties Comparison Apache Phoenix vs. Microsoft Azure SQL Database vs. Oracle vs. Oracle Coherence vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Widely used RDBMS

Oracles in-memory data grid solution

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

phoenix.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/database

www.oracle.com/java/coherence

vitess.io

Technical documentation

phoenix.apache.org

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/en/database

docs.oracle.com/en/middleware/standalone/coherence

vitess.io/docs

Developer

Apache Software Foundation

Microsoft

Oracle

The Linux Foundation, PlanetScale

Initial release

2014

2010

1980

2007

2013

Current release

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

V12

23c, September 2023

14.1, August 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

C and C++

Java

Server operating systems

Linux
Unix
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

Docker
Linux
macOS

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Schemaless in JSON and XML columns

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.

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JCache
JPA
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C++
Java

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

Transact SQL

PL/SQL

also stored procedures in Java possible

yes

proprietary syntax

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

isolation level can be parameterized

configurable

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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

authentification to access the cache via certificates or http basic authentication

Users with fine-grained authorization concept

no user groups or roles

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