DBMS > Apache Phoenix vs. Interbase vs. Microsoft Azure Cosmos DB vs. MySQL vs. Oracle Coherence

System Properties Comparison Apache Phoenix vs. Interbase vs. Microsoft Azure Cosmos DB vs. MySQL vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

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

Light-weight proven RDBMS

originally from Borland

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

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	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

phoenix.apache.org

www.embarcadero.com/products/interbase

azure.microsoft.com/services/cosmos-db

www.mysql.com

www.oracle.com/java/coherence

Technical documentation

phoenix.apache.org

docs.embarcadero.com/products/interbase

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

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

Developer

Apache Software Foundation

Embarcadero

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Initial release

2014

1984

2014

1995

2007

Current release

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

InterBase 2020, December 2019

8.4.0, April 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

Linux
Unix
Windows

Android
iOS
Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

export as XML data possible

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

Supported programming languages

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

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

Interbase procedure and trigger language

JavaScript

yes

proprietary syntax

Triggers

yes

JavaScript

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Interbase Change Views

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency
Immediate 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

configurable

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optionally

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

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