DBMS > Apache Phoenix vs. BigchainDB vs. MySQL vs. OpenEdge vs. Oracle

System Properties Comparison Apache Phoenix vs. BigchainDB vs. MySQL vs. OpenEdge vs. Oracle

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Widely used open source RDBMS

Application development environment with integrated database management system

Widely used RDBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
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

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

phoenix.apache.org

www.bigchaindb.com

www.mysql.com

www.progress.com/openedge

www.oracle.com/database

Technical documentation

phoenix.apache.org

bigchaindb.readthedocs.io/en/latest

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

docs.oracle.com/en/database

Developer

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Oracle

Initial release

2014

2016

1995

1984

1980

Current release

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

8.4.0, April 2024

OpenEdge 12.2, March 2020

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Python

C and C++

Server operating systems

Linux
Unix
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

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

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Schemaless in JSON and XML columns

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

close to SQL 92

yes

with proprietary extensions

APIs and other access methods

JDBC

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Go
Haskell
Java
JavaScript
Python
Ruby

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

Progress proprietary ABL (Advanced Business Language)

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

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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'

User concepts

Access control

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

yes

Users with fine-grained authorization concept

no user groups or roles

Users and groups

fine grained access rights according to SQL-standard

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