DBMS > Microsoft Azure Table Storage vs. OpenEdge vs. Oracle vs. Oracle Berkeley DB vs. Realm

System Properties Comparison Microsoft Azure Table Storage vs. OpenEdge vs. Oracle vs. Oracle Berkeley DB vs. Realm

Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

Application development environment with integrated database management system

Widely used RDBMS

Widely used in-process key-value store

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Wide column store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Secondary database models

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	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

azure.microsoft.com/en-us/services/storage/tables

www.progress.com/openedge

www.oracle.com/database

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

realm.io

Technical documentation

documentation.progress.com/output/ua/OpenEdge_latest

docs.oracle.com/en/database

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

realm.io/docs

Developer

Microsoft

Progress Software Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Realm, acquired by MongoDB in May 2019

Initial release

2012

1984

1980

1994

2014

Current release

OpenEdge 12.2, March 2020

23c, September 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

commercial license available

Open Source

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

C and C++

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

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

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

.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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

runs within the applications so server-side scripts are unnecessary

Triggers

yes

only for the SQL API

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Users and groups

fine grained access rights according to SQL-standard

yes

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