DBMS > BigObject vs. MySQL vs. OpenQM vs. Oracle vs. Oracle Berkeley DB

System Properties Comparison BigObject vs. MySQL vs. OpenQM vs. Oracle vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Widely used open source RDBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used RDBMS

Widely used in-process key-value store

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

bigobject.io

www.mysql.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.oracle.com/database

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.bigobject.io

dev.mysql.com/doc

docs.oracle.com/en/database

docs.oracle.com/cd/E17076_05/html/index.html

Developer

BigObject, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software, originally Martin Phillips

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2015

1995

1993

1980

1994

Current release

8.4.0, April 2024

3.4-12

23c, September 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, extended commercial license available

commercial

restricted free version is available

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

with some exceptions

yes

Schemaless in JSON and XML columns

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Basic
C
Java
Objective C
PHP
Python

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

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

table locks or row locks depending on storage engine

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

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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