DBMS > Adabas vs. IBM Db2 Event Store vs. Lovefield vs. MySQL vs. Riak KV

System Properties Comparison Adabas vs. IBM Db2 Event Store vs. Lovefield vs. MySQL vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

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

used typically together with the Natural programming platform

Distributed Event Store optimized for Internet of Things use cases

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Distributed, fault tolerant key-value store

Primary database model

Multivalue DBMS

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

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

www.ibm.com/products/db2-event-store

google.github.io/lovefield

www.mysql.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Software AG

IBM

Google

Oracle

since 2010, originally MySQL AB, then Sun

OpenSource, formerly Basho Technologies

Initial release

1971

2017

2014

1995

2009

Current release

2.0

2.1.12, February 2017

8.4.0, April 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

JavaScript

C and C++

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux, macOS, Windows for the developer addition

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

yes

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

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

through the embedded Spark runtime

SQL-like query language

via JavaScript builder pattern

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

Supported programming languages

Natural

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

JavaScript

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in Natural

yes

proprietary syntax

Erlang

Triggers

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Active-active shard replication

none

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes, using Riak Security

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