DBMS > Adabas vs. Amazon DynamoDB vs. Hive vs. IBM Db2 Event Store vs. Riak KV

System Properties Comparison Adabas vs. Amazon DynamoDB vs. Hive vs. IBM Db2 Event Store 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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Distributed Event Store optimized for Internet of Things use cases

Distributed, fault tolerant key-value store

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS

Event Store
Time Series DBMS

Key-value store

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

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

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

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

Website

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

aws.amazon.com/dynamodb

hive.apache.org

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

Technical documentation

docs.aws.amazon.com/dynamodb

cwiki.apache.org/confluence/display/Hive/Home

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

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

Developer

Software AG

Amazon

Apache Software Foundation

initially developed by Facebook

IBM

OpenSource, formerly Basho Technologies

Initial release

1971

2012

2017

2009

Current release

3.1.3, April 2022

2.0

3.2.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

Data scheme

yes

schema-free

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP API

JDBC
ODBC
Thrift

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Natural

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

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

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

user defined functions and integration of map-reduce

yes

Erlang

Triggers

yes

by integration with AWS Lambda

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

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

selectable replication factor

Active-active shard replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

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

In-memory capabilities

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

yes

User concepts

Access control

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes, using Riak Security

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