DBMS > Adabas vs. Machbase Neo vs. Microsoft Azure Cosmos DB vs. Newts vs. Riak KV

System Properties Comparison Adabas vs. Machbase Neo vs. Microsoft Azure Cosmos DB vs. Newts 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

TimeSeries DBMS for AIoT and BigData

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS based on Cassandra

Distributed, fault tolerant key-value store

Primary database model

Multivalue DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

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

Secondary database models

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Website

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

machbase.com

azure.microsoft.com/services/cosmos-db

opennms.github.io/newts

Technical documentation

machbase.com/dbms

learn.microsoft.com/azure/cosmos-db

github.com/OpenNMS/newts/wiki

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

Developer

Software AG

Machbase

Microsoft

OpenNMS Group

OpenSource, formerly Basho Technologies

Initial release

1971

2013

2014

2009

Current release

V8.0, August 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Apache 2.0

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
macOS
Windows

hosted

Linux
OS X
Windows

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST
Java API

HTTP API
Native Erlang Interface

Supported programming languages

Natural

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java

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

JavaScript

Erlang

Triggers

JavaScript

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

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Multi-item ACID transactions with snapshot isolation within a partition

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

volatile and lookup table

User concepts

Access control

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

simple password-based access control

Access rights can be defined down to the item level

yes, using Riak Security

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