DBMS > Adabas vs. EJDB vs. IRONdb vs. MySQL vs. Realm

System Properties Comparison Adabas vs. EJDB vs. IRONdb vs. MySQL vs. Realm

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used open source RDBMS

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

Primary database model

Key/Value like access via memcached API

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

github.com/Softmotions/ejdb

www.circonus.com/solutions/time-series-database/

www.mysql.com

realm.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.circonus.com/irondb/category/getting-started

dev.mysql.com/doc

realm.io/docs

Developer

Software AG

Softmotions

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

Realm, acquired by MongoDB in May 2019

Initial release

1971

2012

2017

1995

2014

Current release

V0.10.20, January 2018

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPLv2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

server-less

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

text, numeric, histograms

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 add-on product Adabas SQL Gateway

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

with proprietary extensions

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

in-process shared library

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Natural

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

in Natural

yes, in Lua

yes

proprietary syntax

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

none

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

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

In-Memory realm

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Users with fine-grained authorization concept

no user groups or roles

yes

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